A total of 61 bat specimens belonging to three species were collected from four distinct sites in the middle of Iraq. Five species of acarine ectoparasites on bats were found. These were: Steatonyssus periblepharus Kolenati, Spinturnix acuminatus (C. L. K.). Cheletonella sp. Rhizoglyphus sp., and Argas sp. Three of the recorded species were new to Iraqi fauna. The abundance and accurence of each parasite was varied from one species to another. S. periblepharus aria S. acuminatus were the most common species found in this study.

The aim of the research is to measure the length between the variable the efficiency of the tax examiner with its dimensions represented by (scientific questions, practical process (experience), training and development, impartiality and independence, ethics of the profession) and the approved variable discovering the artificial adaptation of profits, and the degree of arrangement of those dimensions its importance and priority, and the research problem has been identified  In a main question that is there any effect of copying the images of the image examiner in discovering the adaptation, the financial statements and reports of the companies (X, Y) and the banks (A, B) were relied on in the interpretation of the results, t

The study's objective is to find out the difference between the scholar of the research sample in awareness Green nanotechnology on the scaleas a whole and in each of its fields. The research depended of (136) specimen mem and women scholars of the fourth stage scholars / Department of Chemistry at the College of Education for Pure Sciences / Ibn Al-Haytham in Iraq for (2022-2023 AD) for the morning and evening studies, (65%) of the scientific community, It was picked at random with relation to the research instrument. it was a measure of awareness of green nanotechnology of (40) items, distributed in three areas (cognitive, skillful, emotional), and its validity and reliability were verified. Data analysis was completed for utilizing the s

A new, Simple, sensitive and accurate spectrophotometric methods have been developed for the determination of sulfanilamide (SNA) drug in pure and in synthetic sample. This method based on the reaction of sulfanilamide (SNA) with 1,2-napthoquinone-4-sulphonic acid (NQS) to form N-alkylamono naphthoquinone by replacement of the sulphonate  group of the naphthoquinone sulphonic acid by an amino group. The colored chromogen shows absorption maximum at 455 nm. The optimum conditions of condensation reaction forms were investigated by: (1) univariable method, by optimizing the effect of experimental variables; (different bases, reagent concentration, borax concentration and reaction time),     (2) central  composite design (CCD) including

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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

Background: Breast cancer remains a substantial cause of morbidity and mortality, there is a need for continued efforts to understand the etiology of the disease, maintain screening effort, implement prevention strategies, and develop better treatments.Objective: To analyze the risk factors, improve early detection and prevention of breast cancer in Al-Russafa district- Baghdad, aiming to increase survival rate and improve the quality of life.Methods: A cross sectional audit of 258 breast cancer cases seen at Al-Elwiya maternity teaching hospital from January2009 to December 2011,data collected from patients files were: age, gender , residency, marital status, parity, age at menarche and menopause age at first live birth, hormonal therap

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed