Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

This research investigates solid waste management in Al-Kut City. It included the collection of medical and general solid waste generated in five hospitals different in their specialization and capacity through one week, starting from 03/02/2012. Samples were  collected and analyzed periodically to find their generation rate, composition, and physical properties. Analysis results indicated that generation rate ranged between (1102 – 212) kg / bed / day, moisture content and density were (19.0 % - 197 kg/ m3) respectively for medical waste and (41%-255 kg/ m3) respectively for general waste. Theoretically, medical solid waste generated in Al-Kut City (like any other city), affected by capacity, number of patients in a day, and hosp

     Thyroid carcinoma incidence is increasing yearly and ranks second among the top ten cancers in Iraq, especially among women. The single nucleotide polymorphism (rs965513, A>C) near FOXE1 gene was found to be associated with papillary thyroid carcinoma risk in several Genome-wide association studies. Therefore, this is a case-control study aimed at identifying whether this variation is associated with the risk of papillary thyroid carcinoma in the Iraqi population. Association of rs965513 was investigated in one hundred and one papillary thyroid carcinoma Iraqi patients and one hundred and two controls using quantitative PCR-high resolution melting technique. The results of genotype and allele frequencies showe

Background: Animal bite is one of the public health problems all over the world, especially in poor countries. Animal bites have an impact on human health due to rabies disease, which is a viral transmitted disease from animal to human with a high mortality rate.
Objective: To determine the epidemiological characteristics of animal bite cases by person, time, and place.
Method: Descriptive cross sectional study was done by reviewing cases caused by animal bites., Data including the demographic characteristics of age, gender, occupation, site of bite, and attending health institutions searching treatment were all included.
Results: There were 11600 animal bite cases. Most of bites caused by stray dogs 11577(99.8%), and the males

More than 95% of the industrial controllers in use today are PID or modified PID controllers. However, the PID is manually tuning to be responsive so that the Process Variable is rapidly and steady moved to track the set point with minimize overshoot and stable output. The paper presents generic teal-time PID controller architecture. The developed architecture is based on the adaption of each of the three controller parameters (PID) to be self- learning using individual least mean square algorithm (LMS). The adaptive PID is verified and compared with the classical PID. The rapid realization of the adaptive PID architecture allows the readily fabrication into a hardware version either ASIC or reconfigurable.

In this paper, a new type of supra closed sets is introduced which we called supra β*-closed sets in a supra topological space. A new set of separation axioms is defined, and its many properties are examined. The relationships between supra β*-Ti –spaces (i = 0, 1, 2)   are studied and shown with instances. Additionally, new varieties of supra β*-continuous maps have been taken into consideration based on the supra β*-open sets theory. 

In this study, we introduce and study the concepts of generalized ( , )-reverse derivation, Jordan generalized ( , )-reverse derivation, and Jordan generalized triple ( , )-reverse derivation from Γ-semiring S into ΓS-module X.  The most important findings of this paper are as follows:

If S is Γ-semiring and X is ΓS-module, then every Jordan generalized ( , )- reverse derivations from S into X associated with Jordan ( , )-reverse derivation d from S into X is ( , )-reverse derivation from S into X.