IRAQI JOURNAL OF STATISTICAL SCIENCES

This paper sheds light on the theory of chaos, which is one of the latest mathematical theories. Some aspects of the scientific, applied and philosophical fields related to this theory are studied, then focus the spotlight on the solar system as one of the most important natural systems. The chaotic property is studied for three particulate mathematical models fitted the time series of the sunspots, one linear and two non linear. The long-term behavior of these models is examined . It is clear that one of the two non linear models gives similar behavior to the behavior of real data of sunspots. The behavior of this model has chaotic nature, which indicates that the solar system is a chaotic system. It also proposed a computer algorithm which shows the possibility of transmission of a phenomenon from the state of semi-nothingness, to the chaotic state, and then to the order and stability.

In this paper, we concentrate on two cases of fuzzy linear programming problems (FLPP): LPP with coefficient of objective function and coefficient of available resources and constraint are trapezoidal and triangular of fuzzy numbers respectively. Though by using - cut ,fuzzy numbers (fuzzy triangular and fuzzy trapezoidal ) can be transformed into interval numbers and by taking one type of non-linear membership function this meant logistic function, we propose here the "modified S-curve function by simplex method ".

Key words: Fuzzy linear programming, fuzzy triangular, fuzzy trapezoidal, fuzzy number, modified S-curve function, fuzzy simplex method.

In this paper, a new almost unbiased estimator is proposed under stochastic linear restrictions model as alternative to mixed estimator. The performance of the proposed estimator compared to mixed estimator is examined using the matrix mean squared errors.

Keywords: Liu-type estimator; mixed estimator; stochastic linear restrictions.

The methods for solving nonlinear multi-objective optimization are divided into three major categories: methods with apriori articulation of preferences, methods with a posteriori articulation of preferences, and methods with no articulation of preferences. Really there is no single approach is superior. In this paper, a combination between two well known approaches has been used to solve multi-objective GP problems having negative degree of difficulty. First, we use an alternative procedure for converting GP problem having negative degree of difficulty to positive degree of difficulty; second we proposed to discuss all available cases for any number of multi-objective in GP problems using Lexicographic method. This avoids the difficulty of non-differentiability of the dual objective function in the classical methods.

This paper deals with Reliability of Acceptance Sampling Plan (RASP) which differs from ordinary sampling plan for a static quality characteristic,since it involves a non-normal fail time distribution and censored data.The plans consist of the optimal sample size and the critical number of failures which satisfy the consumer and producer risks are determined for a given censoring time.the distribution of life time is Gamma where the shape parameter is known ,plans are tabulated for selected combination of consumer and producer risks and parameter values are achieved by using matlab program written for this purpose.

In this paper we studied and found the stability conditions of the (AEXPAR) model by using a dynamical approach and by adopting the linear approximation technique.

In this paper, we study the statistical and chaotically analysis for the real observations represented by the observations of rainy day falling on Mosul city , diagnose its behavior using some measurements and indicators of statistics and chaos that are applied directly on the time series data by using a new binary technical test, the 0-1 test for chaos, to identify some of the statistical and chaotic characteristics features for the real observations using the techniques and computer simulations represented by time series curve, State-Space Diagram. Periodicity is identified by the spectral analysis, check independence is based on the correlation integral and free statistics by using the statistical indicator BDS, and that supports the diagnosis of conduct for these observations. In this study, real observations for the years 1994-2000. Show, through this paper, that the time series of rainfall in the city of Mosul is not independent and its behavior is non-periodic, chaotic and irregular, this can not predict its behavior in the long time.

The aim of this paper is to give a characterization between the external and internal sets, and some relation between the galaxies and monads, according to this paper we obtain the following results :
 A set is galaxy iff there exists a strictly increasing sequence of internal sets such that .
Also A set is monad iff there exists a strictly decreasing sequence of internal sets such that .
 If is a galaxy and is a monad such that , then there exists an internal set such that .
 A monad is not galaxy.
 If is a monad and is a galaxy, the set of all internal functions such that is a monad)

Keywords: Galaxy, Monad , Internal, External.

In this paper we study a numerical solution of coupled BBM systems of Boussinesq type, which describes approximately the two ways propagation of surface wave in a uniform horizontal channel of length l filled in its undisturbed depth h. This paper is devoted to drive the matrix algebraic equation for the one-dimensional nonlinear BBM system which is obtaining from using the implicit finite difference method. The convergence analysis of the solution is proved. Numerical experiments are presented with a variety of initial conditions describing the generation and evolution of such waves, and their interactions.

The research objective adoption idea came to build and study the state space models to identify the reasons of epilepsy on basis of the brain waves frequency, where two models have been built, the first of which is concentrated on building state space models to estimate epilepsy seizure whereas the second is concentrated on building the state space models to identify the reason of the disease via displaying a statistical procedure programmed on the computer to facilitate the specialist doctors task to stand on the specific reasons of each state so as to enable them to give the patients the correct medicine.

In the present paper, we define a new family of summation-integral Beta operators to approximate a class of unbounded continuous functions of polynomial growth , for some and then we estimate the rate of convergence for this family for functions have derivatives of bounded variation.

In this paper, an operational matrix of integrations based on the Haar wavelet method is applied for finding numerical solution of non-linear third-order korteweg-de Vries-Burger's equation, we compared this numerical results with the exact solution. The accuracy of the obtained solutions is quite high even if the number of calculation points is small, by increasing the number of collocation points the error of the solution rapidly decreases as shown by solving an example. We have been reduced the boundary conditions in the solution by using the finite differences method with respect to time. Also we have reduced the order boundary conditions used in the numerical solution by using the boundary condition at x=L instead of the derivatives of order two with respect to space.

Modified (r, k) class ridge regression (MCRR) which includes unbiased ridge regression (URR), (r, k) class, principal components regression (PCR) and the ordinary least squares (OLS) estimators is proposed in regression analysis, to overcome the problem of multicollinearity. In this paper, we derive the necessary and sufficient conditions for the superiority of the MCRR estimator over each of these estimators under the Mahalanobis loss function by the average loss criterion. Then, we compare these estimators with each other using the same criterion. Finally, a numerical example is done to illustrate the theoretical results.

Key Words: Multicollinearity; Ordinary Ridge Regression Estimator; (r, k) Class Estimator; MCRR estimator; Mahalanobis loss function.

In this paper we introduce a subclass of multivalent harmonic meromorphic functions defined in the exterior of the unit disk by using generalize hypergeometric functions. We derived sufficient coefficient conditions and shown to be also necessary for this subclass by putting certain restrictions on the coefficients, distortion theorem, extreme points and other interesting results are also investigated.


KeyWords: Multivalent functions, Meromorphic functions, Harmonic functions, Distortion theorem, Starlike functions, Hypergemetric functions.

In this paper, some exact solutions for the convection–diffusion–reaction equation in two dimensions and a nonlinear system of partial differential equations are formally derived by using the first integral method, which are based on the theory of commutative algebra.

Keywords: First integral method; two-dimensional convection–diffusion–reaction equation, nonlinear system of partial differential equation.

In this paper we study rightidempotent reflexive ring whose simple singular right R-module isYJ-injective, we prove that this type of ring is right weakly regular ring, we show that if R is N duo or NCI ring and R is right idempotent reflexive ring whose every simple singular right R-module is YJ-injective then R is reduced weakly regular ring

In this paper, a new Spectral Conjugate Gradient (SCG) method for solving unconstrained optimization problems; based on inexact line searches is investigated. The search directions of the new CG method are always sufficient descent. The global convergence property of the proposed method has been proved. Finally, we have presented some numerical results to examine the efficiency of the proposed method.

Most of the time the researcher confronts a decrease in the experimental units required when applying a certain design, this problem appears especially when conducting the factorial experiments which mostly need great numbers of experimental units, to overcome the decrease of the experimental units three incomplete block designs have been used in order to point out which one is best and to know as well the extent of the influence of a number of experimental units on the results of statistical analysis.
A factorial experiment 23 has been conducted on the dry weight of lentil seeds (mg/10 plants) and the experiment factors adopted are: the method of plantation, the locran herbicide and the soil moisture. The experiment of the randomized complete block design has been applied in seven blocks and considered as comparative experiment, from this experiment, the following incomplete block designs have been created were: the balanced incomplete block design, complete confounding and partial confounding.

Several learning algorithms for feed-forward (FFN) neural networks have been developed, many of these algorithms are based on the gradient descent algorithm well-known in optimization theory which have poor performance in practical applications. In this paper we modify the Polak-Ribier conjugate gradient method to train feed forward neural network. Our modification is based on the secant equation (Quasi-Newton condition). The suggested algorithm is tested on some well known test problems and compared with other algorithms in this field.

In this paper, we have discussed and investigated an extended PR-CG method which uses function and gradient values. The new method involves the extended CG-methods and have the sufficient descent and globally convergence properties under certain conditions. We have got some important numerical results by improving a standard computer program compared with Wu and Chen (2010) method in this field.

Al-Sanjary (2001) mentioned the values of mean and standard deviation of the power of hydrogen (pH) and concentration of carbon dioxide (CO2) in the water of Tigris river in Mosul city, the study was applied over five locations during ten months. This information were used to simulate thirty values of each location during each month. The simulated data were used to compare some statistical analyses which are: analysis of variance followed by Student Newman Keules Test to compare between the means, factor analysis with axes rotation and the simple correlation coefficient. The results are presented in figures and charts to simplify the visual comparisons. The statistical analyses approach to the same conclusions. It was concluded that the power of pH and the concentration of CO2 were highly effective in the region of Danadan, also the two variables were increasing in September. However the regions affected the two variables more than that months did.

This paper presents the development and implementation of a new
unconstrained optimization method; based on the inexact line searches. Our new proposed Conjugate Gradient (CG) method always produces descent search directions and has been shown to be a global convergence. Our numerical results are promising in general by implementing ten nonlinear different test functions with different dimensions.

In this paper, we present modified conjugancy coefficient for the conjugate gradient method based on the (Liu and Storey) method to solve non-linear programming problems. We proved the sufficient descent and the global convergence properties for the proposed algorithm for three cases and we get very good numerical results especially for the large scale optimization problem.

In this paper, using algorithm models of Hidden Markov models, it has been concluded that the possibility of recognizing the warp face and the morph face the image real departments face on recognizing object. In through applicability Algorithms model of Hidden Markov and allegation with Algorithm (Beier-Neely) get through in to practicability the defining recognizing the warp face image and the morph face image. The results of hidden Markov models indicate that the matrix at the final iterate able to recognize the warp face and the morph face. Programmers of all algorithm are writhen using the language Matlab (R2008a) 7.6.0.

Conjugate Gradient (CG) methods comprise a class of unconstrained optimization algorithms which are characterized by low memory requirements and strong local and global convergence properties. Most of CG methods do not always generate a descent search directions, so the descent or sufficient descent condition is usually assumed in the analysis and implementations. By assuming a descent and pure conjugacy conditions a new version of spectral Dai-Yuan (DY) non-linear conjugate gradient method introduced in this article. Descent property for the suggested method is proved and numerical tests and comparisons with other methods for large-scale unconstrained problems are given.

This study deals with the prediction of the non-stationary spatial stochastic process. The prediction is done by two techniques which are regression technique (generalized least square estimation) and universal kriging technique. As it is familiar, that the non-stationary stochastic process has a trend (mean) as a linear or non-linear model. By this process we can find covariance function from knowing the variogram function and the latter is attributed to a spherical variogram model, also in order to estimate parameters of spherical model by minimum norm quadratic unbiased estimator which requires that the covariance function must be linear in the parameters, then changing the spherical model into an approximated linear model by Taylor series in the linear approximation
The prediction in these two techniques is applied to real data which represent height levels of ground water of 47 wells with their regional coordinates in Sinjar district in Ninevah Governorate in Iraq. The results were so encouraging where we show the approximation between the predictive values and the real values as well as computing the variance of prediction in these two techniques. It is shown that the prediction variance of universal kringing is less than that of regression.

In this paper, based on the memoryless BFGS quasi-Newton method, we propose a new modified Hager-Zhang (HZ) type method. An attractive property of the proposed method is that the direction generated by the method is always a descent direction for the objective function.
Moreover, if the exact line search is used, the new method reduces to the ordinary HS method. Under appropriate conditions, we show that the modified HZ method is globally convergent for convex and general functions. Numerical results are also reported.

The training phase of a Back-Propagation (BP) network is an unconstrained optimization problem. The goal of the training is to search an optimal set of connection weights in the manner that the error of the network out put can be minimized. In this paper we developed the Classical Fletcher-Revees (CFRB) method for non-linear conjugate gradient to the scaled conjugate gradient (SFRB say) to train the feed forward neural network. Our development is based on the sufficient descent property and pure conjugacy conditions. Comparative results for (SFRB), (CFRB) and standard Back-Propagation (BP) are presented for some test problems.

In this study, new charts were formed using Baysian technique and they were called Baysian chart (2B) , to control the average . The control chart (2B) was used and the process includes real data that involved results of test of the asphalt concrete samples of the base layer used in the construction of new streets. These samples were obtained from the general authority of roads and bridges / The general directorate of roads and bridges in Nineveh province .

In this paper we proposed a new HS type conjugate gradient method by using two kind of modification, first derived a new non-quadratic model second using structure of the memoryless BFGS quasi-Newton method. The new proposed method always generates a descent condition. We give a sufficient condition for the global converges of the proposed general method. Finally, some numerical results are also reported.

Palm print biometrics technology is highest used for human identity verification in most of security application. In this research the automated biometric system based palmprint biometric technique is used. The procedure of implementation is divided into two Stages (Enrollment stage and Verification stage). Each stage is divide into three parts ,the first part is pre-processing techniques based on image requirement and cropping to achieve the better image for palmprint. The second part is feature extraction based on countourlet to obtain a good coaffiention and KL transform to have eign values that reduce the input .The third part is a classifier using backpropagation neural network to authentication. The automated biometric system is feasible, easiest to use, and effective in personal authentication using palmprint features with high detection rate (97% )

This research deals with modeling cumulative number of patients with cancer disease in Nineveh Iraq. The method is based on classes of Exponential Growth Models and uses the ideas of Non-Linear Dynamic Generalized Model(NLDGM). We take three types of ; Modified exponential, Logistic and Gompertz and use the First-order Tayler series to approximate the Non-linear model to a linear model.Also this research, the discount factor has been explainy, and finding forecast distribution and forecast values by using Bayesian forecasting Approach.

In this research an algorithm was suggested for classifying a speaker age to two classes: (young and old classes) based on his speech signal. The suggested algorithm depend on a speech signal feature extraction in order to get a compact representation for this signal and to adopte these features in the classification process.
In this algorithm, the eigen values of the covariance matrix was adopted as a principle parameter in the recognition between the two classes. It was constructed from the data of the speech signal (usually one dimension( after rearranghng it into a number (2,4,8,16,32,64) of a two dimension square matrix array . The suggested algorithm include two main stages:
• 1st stage: includes data file preparation that contains the eigen values for a number of persons belong to both classes young and old (with different gender), in this stage the average of these values for each class to be calculated separately and the threshold curve(which represents the boundary seperating between two classes( were also computed.
Second stage: in this stage the classification process was done by comparing the curve that represents the eigen values of the speech signal, with the threshold curve, a different number of performance parameters are adopted in the evaluation the accuracy of the classification process. The measured correlation value was in range of (0.9610, 0.9994) when m=2 and m=64, respectively (this means whenever the number of arrays that the speech signal constructed from it increases, the correlation coefficient also increases) , while a clear difference can be seen with mmse parameter. After applying the suggested algorithm on 50 persons from both genders, the algorithm passed in applying 80% and failed in percentage 20% of them.

In this paper, The probability distribution of the estimated stochastic ridge factor has been found, which has been developed by adding prior information to the sample information. These information has been represented by the information about the parameters of multiple linear regression model which are in the form of mixed linear model which contains the fixed and stochastic information.

In recent years, secure communication techniques have increased widely and unexpectedly . In order to establish reliable communication technology and to ensure that the data (sound) reaches its intended end and to be accessible to all through the shared network , there is a need to encrypt the transmitted information.
The research was divided into three stages, the first stage included the process of extracting sound features for the file to be sent .In the second stage neural networks were used in the encryption process of the properties resulting from the first phase. In the final phase encryption algorithms were used to encrypt the result from the previous phase. The speech signal of male and female were coded and encrypted. The measures (SNR, PSNR, NRMSE) were used to improve the results. Besides that the Matlab were used as a programming language in this paper.

This paper deals with two problems Bayesian estimation and hypothesis tests to the parameters of Multivaiate- t distrbution when the degrees of freedom of distribution is known with the (informative and non- informative) prior information. The results were applied on the neonatal birth scales data in Nineva Governorate for the year (2005).

Speech compression is very important in many applications. In this research we applied compression on speech by using wavelet transform and contourlet transform. By taking speech (which is often single dimension) into a two-dimensional array (to be suitable for transferring it to contourlet transformation), and then we applied wavelet transform .Then we make contourlet transform on coefficients of high wavelet. After transforming or storing speech and when using the decompression is applied by using inverse way of those transformations. Applied measuring (SNR, PSNR, NRMSE and Corr.) to test performance of the results, the results are very good.

In this study, the construction of a Fuzzy Inference Control to determine the validity of the quality of ground water wells of some of Nineveh province, through a series of observations that were obtained from the areas under study. To illustrate the importance of the model it was compared with the Discriminate Function that classify the individual to the right community. The model , has proved a model of control Fuzzy high efficiency in the determination of the validity of each well is compared to a model Discriminate Function was the only classification of the wells under study where there it is valid or invalid to drink, as well as easy construction of the computational procedures required to build a Fuzzy Inference model compared to complex computational procedures required by the Discriminate Function. The configured model can be used in future to distinguish the quality of any groundwater wells based on qualitative characteristics of the waters.
Keyword: Fuzzy Control, Discriminate Function, groundwater.

Hiding processes in Linux system is an essential part of rootkits actions and malicious program. So, it is very important to monitor and administrate the system hidden processes to ensure the safety and reliability of the computer system. Also, process administration can be a vital factor in determining the stability of a running system.
The aim of this research is to detect hide processes in Linux system depending on /proc system files and offer tools for monitoring these processes in addition to monitoring and administrating all other processes in the system to ensure that the required processes are running and that the total number of each type of running process is appropriate to maintain system stability.
The software offers capability for displaying processes in the system including hidden processes with full information about them. And it offers options for killing or suspending a process, change process priority and viewing the memory map and the memory status for a given process.
The work has been run successfully on Linux operating system, Ubuntu distribution, version 10.4, and developed using C++ GUI programming with Qt 4 package and number of shell commands.

In this research, a solution of heteroscedastisity of the random error variance is found in the Multiple Logistic Model when the response variable (dependent) variable is Qualitative by using the method of weighted least squares (WLS) to estimate the parameters of the Multiple Logistic Model, which depends on the weights estimated Empirical Bayes method and compared with the Classical method through some statistical criteria (Mean Square Error (MSE), Coefficient of determination and the F test), so as to obtain the best possible estimate of the parameters of this model through practical application deals with the study of the relationship between the number of recovered patients of severe acute renal concentrations of different types of medicines and are (Ciprodar) and (Garamycin) was given to them in the Republican Hospital / Erbil, and through the design of a program language MATLAB to calculate the weights of Bayes and depend on the statistical package SPSS in the procedures of regression analysis.

This research detects the existence of the face in the digital images by using an Elman network, after a number of stages where at first it converts the image to the gray level and then segmentation of image which is based on the characteristics of the skin algorithm for segmenting the skin by extracting the properties of human skin using amulti-colored skin bilateral algorithm and then entering the data to a neural network. The algorithm was applied to a number of different models and proved to be efficient and accurate in detection reaches 90% depending on the results .
Keyword : face Recognition, skin detection, Neural network

Protection of digital multimedia content has become an increasingly important issue for content owners and service providers. Watermarking is identified as a major means to achieve copyright protection.
This watermarking algorithm is based on the Discrete Wavelet Transform (DWT). Watermark components are added to a high frequency subband by considering the human visual system (HVS) characteristics. HVS characteristics are used in this scheme to develop a robust watermarking scheme with a better tradeoff between robustness and imperceptibility. A visual mask based on HVS characteristics is used for calculating the weight factor for each wavelet coefficient of the host image.
The proposed scheme was tested against mostly known threats and it proves to give good robustness. Also it still gives a high quality watermarked image. MATLAB Program was used to perform the watermarking task.

This research suggested a new heuristic method to select the best regression equation. Assuming that we have a set of predictor variables. The choice of some of those variables is required to obtain the information that we get it if we used all those variables. The research presents the used methods to select the best regression equation also presents a new method that depends on the partial correlation coefficient. This paper compares the new method with stepwise regression procedure by using real data depending on criteria mean square error (mse).The new method showed ease of use and high efficiency.

This work presents design, modeling, simulation and hardware implementation of a separately excited DC motor speed control using Field Programmable Analog Array (FPAA) Technology. The framework presents a low power self-tuning analog Proportional-Integral-Derivative (PID) controller using a model-free tuning method, this overcomes the problems associated with reconfigurable analog arrays. In comparison with a self-tuning digital PID controller, the analog self-tuning PID controller combines the advantages of low power, no quantization noise, high bandwidth and high speed. The prototype hardware uses a commercially available field programmable analog array and Genetic Algorithm as tuning method. The practical results show that a self-tuned controller can outperform a hand tuned solution and demonstrate adaptability to plant drift, also it shows enhancement in the reduction of overshoot, settling time and the steady-state transient response of the controlled plant.

The research aims is structuring the TMJ clinic; it is a computerized system that diagnoses and treats the clinical cases through a computing statistical basis for the serious cases.
This system helps to take broad decisions broad in dentistry and in diagnosis.
Artificial networks have been used to find first the major exponents of the TMJ diseases, in order to exploit a training basis (Hebbians Network) to help to shed light on the affecting variance as to get almost less variance with a large amount of information. second to show how the variables under discussion interact and cause specific outcomes. We use BBN and we have some conclusions about this .
The current system has a proper of being quick storage and restoration,and updating the information for each patient, as well as new items benefit & inhgacate all patients.
The system includes a general and specific statistics for individual patients or clinics, and it is interchangeable spontaneously according to the case. There are several queries and reports.
This system has been followed on (80) patients from the outpatient dept. of Al-Salaam university Hospital/Dentistry college / TMJ unit at Mosul University.
The possibility of application has been suggested to the private and general clinics.
Database has been designed by Microsoft Access and programmed by visual Basic V.6.0.

In this paper we study the stability of one of non-linear autoregressive models with trigonometric terms , by using the linear approximation technique . From this method the singular point and the stability of the limit cycle for this model has been obtained . We applied such results to some time series data

In this paper we consider the motion in thin liquid films of a rectilinear flow by inertia force and there is a balance of pressure gradient, viscous and surface tension.Navier – stokes equations and continuity equation are used to obtain the equation that governs this type of flow.

In this paper, we solve one of the parabolic partial differential equations in three dimensions which is heat equation with Locally One Dimension methods, and by comparing the results by this method with the exact solution, we see that the results are nearest to the solution and specially of the implicit method (Crank-Nicholson). Then we study the numerical stability, numerical consistency and numerical convergence of these methods which shows that it’s unconditionally stable with (C-N) and conditionally stable with explicit scheme. Consistence and converge are realized.

In this paper, we use the approximate solution of linear partial differential equations in three dimensions of the parabolic type by using Adomian Decomposition Method (ADM). Comparing the numerical results of method with result of the exact solution we observed that the results correlate well and are very close.

This paper is devoted to analyze the stability of the flow of a aqueous humor in posterior chamber of the human eye. This analysis is done by finding the eigenvalues of the system which enable us to investigate the growth of disturbance after setting the system of equations, of a aqueous humor in the posterior chamber of human eye, in linearization form. The reason behind this distribution is due to the difference in temperature between the inner surface of the cornea and the iris. We conclude from the analysis results that the equations are stable when the real part of wave velocity is negative whereas unstable when it is positive.

The aim of this paper is to analyes the stability of a system of flow and evaporation liquid of tear film throw the pre-lens tear film (PrLTF) of contact lens in eye porous layer which infected by dry-eye (dry eye syndrome) and this analysis was done by using Galerkin method which enables to find disturbance growth from it’s nonexistence after making the system linearization we find the parameters which affect the increase of the density of tear film and as a result reduces the evaporation operation that cause this disease.

This research deals with the actual medical data including a number of variables such as Systolic Blood Pressure (SBP) Total Cholesterol (TC) and high density lipoprotein .a computer system is constructed depending on the fuzzy logic ,which classifies the risk value of health status for each patient after feeding the input of the above mentioned variables. By application of this constructed system on the actual medical conditions it is found that it gives medically accepted results of more reality than the results which do not depend on the fuzzy logic.

In this paper the probabilistic multi-item inventory model is derived when the holding cost is a function of the order quantity, and restricted by a non-linear restriction imposed on this cost. The demand during the lead time is a continuous random variable that follows some continuous distributions. Lagrange Multipliers Method has been applied for the purpose of the model analytical processing

In this paper, one of the artificial intelligence algorithms was used, which is the genetic algorithm that is based on the application of innovative concepts including selection, crossover and mutation. A genetic algorithm was suggested for the static games to find the equilibrium and to estimate the asymptotic least squares was suggested, and we obtain good results in comparison with the ordinary algorithm. The application of the genetic algorithm on static games led to finding several solutions according to the times of simulations that represent the optimum solution ( the optimum value of equilibrium).

In this paper the probabilistic multi-item inventory model is derived when the holding cost is a function of the order quantity, and restricted by a non-linear restriction imposed on this cost. The demand during the lead time is a continuous random variable that follows some continuous distributions. Lagrange Multipliers Method has been applied for the purpose of the model analytical processing

In this research, classification of(24) wells in the aquifer of water existed within the Pilaspi Geology Formation in the Bashiqa area ‎/ North of Mosul, by using one of the types of artificial neural networks and specifically (kohonen network(,by depending on groundwater quality. Where achieved the use with some the software of the computers, including Global Mapper v.7, which had been determine the wells locations for the groundwater on the topographic map of the research area according to the latitude and longitude coordinates for utilization from it is statistical in the classification process, Also we use's software C++ v.3, who is use Programming of Kohonen network for the classification of those wells with intelligence technology to groups according to Electric Conductivity (E.C) in the water.

This research has proposed an algorithm to find the optimal schedule for three jobs in flow –shop environment with three stages , so that the makespan is less than what can be.

This algorithm is based on the linear programming approach in computing the makespan ,the objective function and constraints have been formulated under the conditions of precedence between operations in flow shop environment .
After applying this algorithm on several problems which are generated randomly by uniform distribution ,the results showed that the makespan which is computed by the proposed algorithm is equivalent to other scheduling algorithms .

According to the development in computing industries and production Management ,in this research we focus on the design and application of of the main stages of production , a phase of cutting the 2D with standard measurements and virtual cutting , depending on the Bill Of Materials(BOM) of one product or the product order in order to achieve an optimum cutting and optimum parts distribution on the boards at less number of boards at less worst rate and showing it to technical engineer as a two-dimensional figure using autocad. Several attempts (probability)were tried to distribute the parts on the board at random in order to achieve an optimum distribution of BOM depending on the design and application of genetic algorithm which is one of the intelligent techniques with suggestion of cutting algorithm as a mechanism for virtual cutting characteristic of designed system, It can be applied in several plants (iron and steel /furniture/aluminum/ glass/ clothing/journals and magazines/containers/water tanks.), and also features the possibility of rotating some of the parts to achieve optimum cutting . The system was designed using visual basic .net , oracle 9i and autocad2007.

In this paper, a new steganographic technique was proposed. First, the cover colored image (of type BMP, PNG) transfered to a gray image, then the result divided into many blocks to embed the secret message in an optimaized method by GA (Genetic Algorithm) after using the LSB (Least Significant Bit) technique. The STD (Standard Deviation) was calculated for each block of the image blocks before and after embedding operation besides that the results were compared together, then the GA was used to obtain the Optimized value for the PSNR (Peak Signal-to-Noise Ratio) measure. To improve the performance of the results many measures were used such as BER (Bit Error Rate), MSE (Mean Sequare Error) and PSNR. The implementation was done using Matlab 9b as a programming language because of it's perfect Library of GA.

By research, three methods for hiding secret message were proposed. In the first one the secret message was hid in a known DNA sequence belongs to prokaryotic organism Escherichia Coli k12 (E.Coli ) DNA sequence obtained from EBI location (European Bioinformatics Institute), Among the DNA molecule characters, one of the mutant ability types, that is the silent mutant, was chosen to hide a secret message within the sequence. The second method, a sequence of DNA has been synthesized chemically depending on the text secret message via using tables of symbols formed from English letter, numbers and special characters, each symbols represents codon and the symbols were arranged in the table in descending order depending on English letter frequency codon frequency (Genes). While in the third method the secret message was hid in E.Coli bacteria with known nitrogen base sequence in EBI using complementary character.
The proposed methods applied in Matlab program and C# . Results of study revealed that DNA sequence has a high ratio for hiding secret message. The results reached 100% and the error rate to 0%.

The process of recognizing the processed patterns makes the pattern data useful for the computer. It plays a significant role in the field of pattern recognition and computer vision. So, the image capture is an inaccurate process in terms of the distance from the object. Therefore, the image capturing for object from the inside of a moved vehicle, for example, will lead to a change in the distance between the object and the vehicle for each captured image and finally a change in the size of the object image size inside the image. Viewing that the techniques of chain coding are considered the most used in presenting. Therefore, this study has recognized the patterns inside the image by using the chain coding .In the paper, the most important problems that the application of recognizing patterns by using the chain coding and the methods of solving them have been presented .The chain coding has been applied on the images of the regulated and the unregulated geometrical patterns .The problem of changing size has been solved by a suggested method and this method has proved to be of high efficiency in recognizing the patterns of various sizes .Also, the method has proved a higher efficiency compared with Rehman to process the size changing in which the chain coding is used.

The immense development in the communication network has opened new spheres that threaten the data security transferred via the communication networks. As a consequence the techniques of encryption and information hiding and merging them to increase the security of data sent.
The paper presents suggestion and design for a system to send data secretly by merging encryption technique and information hiding using steganography technique and covert channels to hide the data. The secret data needed to be sent encoded by using Data Encryption Standard (DES) algorithm or by Triple Data Encryption Standard (TDES) algorithm. Then the encoded data were hidden in a form of colored image of BMP type using Least Significant Bit technique (LSB). The covert channels of Voice Over Internet Protocol used its type value based spatial channel and active behavior to send the stego-image or text file using )Session Initial Protocol(SIP) Session Description Protocol(SDP) Real-Time Transport Protocol (RTP), Real-Time Transport Control Protocol(RTCP)(. The results have been retrieved hidden information properly for all the protocols.
The hiding in image was done by using one slide or three slides of image in one bit or two bits or three bits where the transfer taken place from one pixel to another either by using one key or two key or three key. It is concluded that the hiding in one bit given less error value but with longer execution time that is the value of MSE depends on the number of bits were changed and by using multiple keys to increase the secrecy with the guarantee of not losing the data. Visual C# and Matlab7.6 (R2008a)were used in the programming.

In this research we used a new method to distinguish the Arabic letter, depending on the different sizes of the Arabic letter and apply to all Arabic letters similar and dissimilar and took the character movements (opening, Vibrio, and Kasra) and will reach a good results.
proposed algorithm working begin by introduce the Arabic letters, and a preliminary treatment in the image of the Arabic letters .in this research will be studied (matrix of a co-occurrences and characteristics of the matrix) as a parameter to distinguish the Arabic letter and give strong rate of recognition, applying network (perceptron) and a network (Back probagation) in order to speed up the process of recognition and make comparison between performance of the two networks.

Departments colleges suffer from the problems that exist in the system of traditional advertising based primarily on the use of bulletin boards and the manner in which the paper is characterized by extravagant and might not read the advertisement in time for the persons concerned. For that, an advertisement system has been developed using mobile SMS technology. This system consists of two main parts, the first sends the results of students taken from the database in the examination committee and send through the mobile as text messages as well as to via e-mail immediately after the completion of the procedures necessary to the posting. The second part of the system is an advertisement system between the head of the department and the department committees, also can be between all the employees of the department.
The system has been tested in the Department of Computer Sciences at the College of Computer Sciences and Mathematics at the University of Mosul, and the results were identical to the research.

The increasing growth of the multimedia on the network led to increasing the need to offer efficient methods to protect data and the individual property. The aim of hiding the information is to remove the suspection in the existence of a hidden information and the special thing in the technique of hiding information is that it conveys the modern techniques and protects the messages and reduces the necessary area to save it in a file or sending then on the net the technique of press. So, in this research a method of hiding was suggested depending on Karhunen Loeve information and using the method of (RLE) Run Length Encoding for pressing the resulted data and applying the method of (LSB) Least Significant Bit for hiding the data by using a random formula in choosing a location for saving the information in a covering image. The method showed a high efficiency in pressing and hiding in the digital images.