IRAOI JOURNAL OF STATISTICAL SCIENCES

The problem of finding genetic mutations is an issue of special
importance for its relationship with genetics evolution of living
organisms. In this paper we present three statistical methods proposed
for the creation of genetic mutations, the first depends mainly on the
Markovian model، the second on the autoregressive models, and the
third depends on the algorithm proposed based on the hidden Markov
model. The three methods are applied to DNA for sequence with
shortage oxygen of humans, and shows the practical application show
that of these methods give good results in the detection of genetic
mutations, reached in some cases to 90%.

In this paper eigenvalue of a gray image is used for
image segmentation by calculating the eigenvalue for
each segment and to be compared with a threshold value
[which will be calculated dynamically by the system] and
an iteration procedure will continue running until
saturation arrived.
By using the quadtree technique the gray image is
divide into small segments depending on the value of the
threshold and then the segmented image will pass into low
pass filter in order to produce more enhancement in the
image .
The algorithm was applied on different types of
images [natural images , text images] and both of them
give high quality of segmentation .

The non-linear conjugate gradient method is a very useful
technique for solving Large-Scale minimization problems and
has wide applications in many fields . In this paper, we present a
new spectral type, a non-linear conjugate gradient algorithm the
derivatation of this algorithm is based on Fletcher – Reeves and
Newton algorithm, the descent property for the suggested
algorithm is proved provided that the step size satisfies the
Wolfe conditions. Numerical results show that the new
algorithm is efficient in practical computation and superior to the
Fletcher – Reervs algorithm in many situations.

This Paper deals with the recursive identification problem
of stochastic linear dynamical systems , Important Algorithms
are explained in the identification system domains that are time-
varying, and using a recursive Least Square method with a
famous approach to estimate the model parameter, that a
forgetting factor, and a Kalman filter approach with different
values for a best linear dynamic models, that are identified from
the two type of stochastic linear dynamic systems: that the
equation error models which contain ARX models and ARMAX
models. Output error models which consist of OE and Box-
Jenkins models, that are reached by using the suggested
instrument in Off-Line Identification, where the exact Linear
models reached their parameter stable with Time, Moreover, the
Statistic terms are verified from a point of random errors and
insignificant cross-correlation between inputs and outputs
residual.

In this research the covariance matrix which was used in so
many fields, its eigen values adopted to be the main parameters
for Latin printed character recognition.
The idea was divided in two stages. The first stage is to
generate the covariance matrix then, evaluate its eigen values to
build main table for the whole latin characters in addition to the
numeric values. The second stage is the recognition stage, which
achieved to any character that was entered.
The applied examples do not register any negative result. So
it can be strongly recommended for printed character recognition

This paper deals with the problem of estimating the order of
Markov chains. An algorithm is proposed for this purpose and
programmed by MATLABR2009a, such that the maximum
order is selected automatically after inputting of observations
and the upper limit of the order. A simulation study is carried
out to verify the efficiency of the algorithm, then the algorithm is applied to the observations of rainfall in the city of Mosul for
the years 1994-2000 .It is clear from this application that the
daily rainfall in Mosul city is with order 1.

In this research we display some information criteria for
time series like AIC,BIC,AICc and others. Beside that a proposal criteria is NAICc , two methods have been used for
comparison of performance criteria by simulated and real data
and we got encouraging results

This work deals with descriptive summary of linear
programming subject, and describes least square method for
estimating regression parameters. As well as using other
methods in order to estimate the parameters unconventional on
reduced variance (or reduce sum of square error) , but depend
on minimizing variation of absolute values from the median , the
aim of this work is to find an easy and precise way to estimate
the absolute deviation , which is important when the variance
fail in precise estimate and lead to enlarge the variation of the
data , while least square method depend on minimizing sum of
the square , therefore , the goal is to reduce the deviation of the
absolute values from the mean in model of linear programming
in order to estimate absolute deviation which is a simple and
precise method , and this manuscript includes examples of this
application

In this research a Distributed Computer System Application
for Traffic office has been designed, by using two models of
building Distributed Systems which are: Client/Server Model and
File Transfer Model, and Two organizations for designing
Distributed Databases which are: Central Database with multiple
access from several sites , and the organization of Partially
replicated databases.
We Designed a Multimedia Database and used it to store the
required data including images of vehicles and their owners in
tables of the Database, with the ability to extract Statistical
Information and display it in the form of tables and charts.
A database driven web site has been created, using the
concepts of Web-Databases; the site provides the ability to query
for the data of vehicles and their owners in other provinces.
The designed system is homogenous and uses computer
devices of type (Pentium IV) as hardware and (Windows)
operating system as environment.VFP 9 Language has been used
for programming the application, and also as DBMS, the web
pages have been Designed using ASP technique, and it's code
written using VBscript and HTML Languages

In this research, genetic algorithm is used to solve Queuing
problem, which is considered to be of special importance as a
result of the costs emanating from waiting and operating, is
suggested. The problem aims at locating the period of time for
waiting on the distant range and making this period of time as
less as possible .The application of this genetic algorithm to this
problem led to limiting the most ideal number of the people
served and making the total cost concerning the party who offers
the service as less as possible during the period of time specified
for waiting.

In this research we study the fuzzy nearest neighbor method
(FNNM) for time-series prediction , this method depends on
fuzzy membership value .The main goal of the prediction
algorithm is to forecast future value depending on past nearest
neighbors value. The nearest neighbors that we choose by using
fuzzy membership value or portmanteau membership value .
To measures the accuracy of our method and to compare with
ARIMA model we use mean absolute percentage error (MAPE)
and mean square error (MSE) that is calculated from the actual
value of time series data and the number of internet users and forecasting value. The results encourage using fuzzy nearest
neighbor in forecasting

Is in this research the ordinary least squares method is
reviewed and a brief account on the multiple linear regression
model and regression quintile is given and then study the
characteristics of the society and extracting information from
them to add to the information data to get the multiple regression
model which has less error than original after the addition of
information of population, using regression quantile and
comparison between the results using criterion Mse

The main objective of this study is to select the best
multiplicative seasonal model of the time series data using some
information criteria; they are AIC, BIC, AICC, and SMAIC.
Then prediction is made for the different models and calculates
the final prediction error criterion to ensure the accuracy of our
best selected model. In our study we select the model
ARIMA(0,1,1)(0,1,1) 12 as the best model for the wind speed
series t1,X and the model ARIMA(0,1,1)(0,1,1) 12 as the best
model for the cloud series t2,X .

In this research the relation among rain , temperature and
relative humidity in Mosul city of the time 1988-2001 was
determined by applying Granger test to determine and measure
the direction of the causative relation among the variables of the
research. To make clear whether the chain is stable or not there was a need for using units root test to check the characters of
time chains of the sample variables to know the extent of their
stability and determining the degree of integrity of each variable
alone. The results showed that the variables were highly
integrated so , due to that the joint integrity test was used to
determine he existence or the absence of the longterm relation
among the variables under the study. The analysis showed the
absence of the joint integrity among the variables of the research,
besides the instability of remains of the joint integrity equation
.Also , passage analysis was used to show the causative relation
among the variables under the study and this test boosted by
results we came up with by applying Granger test.

In this research we use path analysis to study the variables
affecting the scientific level of institute students. Data were from
the Technical Institute of Nineveh Examination Committee for
students of the first stage Department of Financial and Banking
for the academic year 2008-2009 which contains eight
independents variables represent study materials and dependent
variable which represents of student final average and the
sample size is (76) students, and then path analysis is applied by
configuring the proposed causal models and then used Stepwise
Regression method for a sample estimator for each proposed
model using the SPSS Ver. (17) and the program AMOS Ver (5)
to find the of direct and indirect effects and total effects for all
estimated models, as well as charting the nets of all models using
the AMOS results and through the clear importance of the
variables first X1 (Internal Banking Operation) , followed by the
third variable X3 (Financial Economic) followed by the second
variable X2 (Financial Reading) , and finally the fifth variable X5
(Risk Management) in effect on the variable Y (the average of
student final).

The use of the Excel program is not only limited to the
usual functions and to formulate and solve linear programming
models, but beyond that it can be used in the applications of
operations research, such as transport problems of the qualities of
random in the needs dialing locations in some cases because they
are not known for sure, especially when accompanied by imposition of additional constraints for the supplier to impose
sanctions when processing more or less than needed.
This paper reviews the architecture of the mathematical
model of the problem of transport and indicate the method of
random use Excel in a possible solution to the problem to reach
the optimal solution quickly and accurately through the property
Solver in this program, where the proposed method has been
applied to several different examples in the numbers of offer
sites and demand sites

This paper aims to display the concept of beta regression
and modality of its utilization in the statistical application by
considering the values of the response variable which are
constrained by the interval(0,1) and the response variable is
following beta distribution. Both Akaike and Bayesian
information criteria are used to get the preferable model by
applying the multiple beta regression in investigating the
percentage of the sugar proportion of the resultant humid spoil to the sugar proportion of the resultant crude juice. We used
statistical software R to obtain the expected results