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

The platforms of social networking sites, with their distinctive communication and technological features, create a social movement that led to the establishment of a new pattern of communication in a modern context. This allows the users on the internet to carry out many social interactions based on the interests and commonalities among them. Algerian women have a share of this digital presence by representing their views and discussing their issues on several sites like Facebook, for example.
In this research, we have analyzed the pages of Algerian women on Facebook site to find out the most important issues addressed by Algerian women so that we can organize their concerns in the digital channels and discover their different orie

Objective: The study aims at evaluating the psychological support and discharge plan from the hospital provided by nurses for woman undergone hysterectomy.
Methodology: The study uses descriptive design and non-probability (convenient) sample which is consisted of (40) nurses from (8) teaching hospitals in the City of Baghdad within the maternity wards. The study is carried out from 11 November 2020 to 27 June 2021. A observational tool is developed to evaluate the psychological support and the discharge plan after surgery. Content validity and internal consistency reliability are determined through pilot study. Data are collected through the use of the questionnaire and data are analyzed through the use of descriptive and inferentia

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin