Nowadays, information systems constitute a crucial part of organizations; by losing security, these organizations will lose plenty of competitive advantages as well. The core point of information security (InfoSecu) is risk management. There are a great deal of research works and standards in security risk management (ISRM) including NIST 800-30 and ISO/IEC 27005. However, only few works of research focus on InfoSecu risk reduction, while the standards explain general principles and guidelines. They do not provide any implementation details regarding ISRM; as such reducing the InfoSecu risks in uncertain environments is painstaking. Thus, this paper applied a genetic algorithm (GA) for InfoSecu risk reduction in uncertainty. Finally, the ef

In this paper, two of the local search algorithms are used (genetic algorithm and particle swarm optimization), in scheduling number of products (n jobs) on a single machine to minimize a multi-objective function which is denoted as  (total completion time, total tardiness, total earliness and the total late work). A branch and bound (BAB) method is used for comparing the results for (n) jobs starting from (5-18). The results show that the two algorithms have found the optimal and near optimal solutions in an appropriate times.

Owing to high antibacterial resistance of Pseudomonas aeruginosa, it could be considered as the main reason behind the nosocomial infections. P. aeruginosa has a well-known biofilm forming ability. The expression of polysaccharide encoding locus (pelA gene) by P. aeruginosa is essential for this ability. The purpose of the current research was to determine the biofilm formation in P. aeruginosa isolated from clinical samples and to evaluate the role of the selected PelA gene in biofilm formation using PCR method in Iraqi patients. Results revealed that 24 (96%) isolates were found to have the ability to form biofilm that was remarkably related to gentamicin resistance. Moreover, the pelA gene was found in all biofilm-producers. In c

Background: The antimicrobial resistance is one of the most serious and expanding health problems world -wide in the last decades. The esbl escherichia coli. (extended – spectrum beta-lactamase e.coli) represents an important aspect of it .Objectives: To get an overview on the esbl e.coli prevalence profile in general. Also to assess the antibiotic sensitivity of esbl e. coli trying to specify the most effective antibiotics in combating this micro-organism.Methods: this study tries to focus on this problem in Iraq which through a prospective study approach by taking 35 clinical samples from various sources (urine, blood, abscess, eye ,vagina ,stool and others),and after confirming the presence of e.coli, the presence of esbl e.coli and

For the period from February 2014 till May 2014, one hundred and nine lactose fermenter clinical isolates from different samples (urine, stool, wound swab, blood, and sputum) were collected from Alyarmok, Alkadimiya, and Baghdad teaching hospitals at Baghdad governorate. Identification of all Klebsiella pneumoniae isolates were carried out depending on macroscopic, microscopic characterizations, conventional biochemical tests, and Api 20E system. Fifty-three (48.62%) isolates represented K. pneumoniae; however, 51.73% represented other bacteria. Susceptibility test was achieved to all fifty-three K. pneumoniae isolates using five antibiotic disks (Ceftazidime, Ceftriaxone, Cefotaxime, Imipenem, and Meropenem). Most of tested isolates (90

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

Background: Prolactin is a hormone, as well as a cytokine which is synthesized and secreted from the anterior pituitary gland and various extra pituitary sites including immune cells under control of a superdistal promoter that contains a single nucleotide polymorphism -1149 G/T. Rheumatoid Arthritis has been associated with increased serum prolactin levels.Objectives: To investigate the association of the extra pituitary -1149 G/T promoter polymorphism among Iraqi rheumatoid arthritis patients and prolactin levels.Methods: We tested 73 patients with rheumatoid arthritis and 40 healthy individuals. The DNA samples were genotyped using the Polymerase Chain Reaction-Restriction fragment Length Polymorphism method and the levels of prolacti

The wide spread of Computer Based Test in the Iraqi universities raised an important concern for some scholars thinking about integrating computers as an academic assessment tool before making big change in the examination systems, that concern is: how the computerized test score is effected in comparison to old paper and pencil . This paper researches whether test scores of Iraqi students varies in the computer, Pencil based tests, sixty-four postgraduate graduates from Iraqi universities. Thirty five female and twenty nine male, all graduated from colleges of science in specializations other than computer science and applying for postgraduate studies in the Iraqi