The current study aims to investigate the relationship between lipid peroxidation, represented by seminal malondialdehyde (MDA) level, and integrity of sperm plasma membrane, represented by the hypo-osmotic swelling (HOS) test score, in infertile men. One hundred and twenty Iraqi men (20 fertile and 100 infertile) shared in this study during their attendance to the High Institute for Infertility Diagnosis and Assisted Reproductive Technologies/Al- Nahrain University. The mean age of the fertile men was (30.46±0.78) years while the mean age of infertile men was (32.58±0.64) years with the duration of infertility (5.36±0.33) years. Semen samples were collected and the parameters of seminal fluid analysis were assessed; also, the HOS

One-hundred and twenty Iraqi women (60 single women and 60 married women) with age ranges from (17-49) years have been involved in this study to estimate the levels of anti-mullerian hormone (AMH) and follicle stimulating hormone (FSH) as markers of ovarian aging. The descriptive data [age, body mass index (BMI), age at menarche, duration of menarche] have been recorded. Blood samples were collected from the studied women to determine the levels of AMH and FSH. The results revealed non-significant (p>0.05) differences in levels of AMH and FSH between single women and married women. A significant negative correlation was observed between AMH levels and age in single women (r=-0.519, p<0.05) and married women (r=-0.433, p<0.05). A no

Adsorption of Chlorophenol compounds in aqueous solution on Iraqi siliceouns rocks powder have been investigated. UV technique has been used to determine the adsorption isotherms. The results showed that the adsorption isotherms obeyed Freundlich adsorption equation. The adsorption was endothermic process, increasing temperature leads to increasing adsorption.  H,  S,  G were calculated. The results showed that the adsorption increases with increasing acidity of solutions

Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,

            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att