Objective(s): 1- Assess the effectiveness of health educational program on nurses' knowledge toward Hemodialysis at Pediatric Teaching Hospitals.

 2-To find out the relationship between nurses' knowledge about hemodialysis and their demographic Characteristics.

Methods: The study was designed in a pre-experimental pattern for the nurses' working in the Child Welfare Teaching Hospital and the Child's Central Teaching Hospital, and a targeted sample consisting of (30) nurses was selected. It is tested in three periods of pre-test, the first post-test, and the second post-test. Participants were tested before implementing the tutorial (tutorial lectures

Objective: To evaluate nurses' practices toward coronary artery bypass grafting (CABG) patients in the
intensive care units (ICU) and to find out the relationship with some vanables.
Methodology: A purposive sample of (50) staff nurses was selected out of three hospitals for cardiac surgery.
The study instmment consisted of two major sections was constructed. It is based on the review of literature.
First it is concerned with demographic data for nurses; and the second section is observationaL tool (checklist) is
composed of six parts in which there mere (78) items. Reliability and validity of the observational checklist were
determined through the analysis of a pilot study.
Data were collected through the use of the

Objective: To determine the effectiveness of the Nursing Management Education Program upon the Nurse
Managers' Knowledge about planning in Nursing Management at Baghdad City Hospitals.
Methodology: A Quasi-experimental study in which a purposive "non-probability" sample of (50) Nurse
Managers was selected from Baghdad City Hospitals. These Managers were divided into two equal groups of
(25) Nurse Managers for each (study and control ones). A questionnaire was developed as a tool for data
collection. A pilot study was carried out to test the reliability of the questionnaire for the period from April 2nd to
June 20th 2007. The pre-post test approach was applied to the study and control groups as mean for the quasiexperime

One of topics that occupied alarge area  in Iraqi  society  at the moment is the  issue( of tribal  separation and its  relation  to the organization of  the community ) so we see in the civilizations and heritage  of each community aset  of provisions and laws that take the form of status   customary or religious it is indicative of the great interest in Iraqi society in cotrolling the behavior of individuals to comply with values and social laws and become their behavior is consistent with the behavior of the total and adhere to the social values and be productive individuals within  the subject and this can only be  achieved  from the social co

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