In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from the whole features set. Thus, it obtains efficient botnet detection results in terms of F-score, precision, detection rate, and number of relevant features, when compared with DT alone.
Gestational diabetes mellitus (GDM) is a growing health concern that usually appears during the second and third trimester stage of pregnancy and is characterized by carbohydrate intolerance of variable severity. The aim of the present study was to scrutinize the relationship between the G972R polymorphism of the insulin receptor substrate-1 (IRS-1) gene with GDM in the Iraqi female population. One hundred and twenty of blood samples taken from healthy women (control) and women with gestational diabetes mellitus in 3rd trimester stage of pregnancy, fasting blood glucose (FBG) and HbA1c% measured to diagnose GDM, lipid profile (cholesterol, triglyceride, HDL, LDL, and VLDL), insulin concentration, insulin resistance and beta cell function to
... Show MoreThe fingerprinting DNA method which depends on the unique pattern in this study was employed to detect the hydatid cyst of Echinococcus granulosus and to determine the genetic variation among their strains in different intermediate hosts (cows and sheep). The unique pattern represents the number of amplified bands and their molecular weights with specialized sequences to one sample which different from the other samples. Five hydatitd cysts samples from cows and sheep were collected, genetic analysis for isolated DNA was done using PCR technique and Random Amplified Polymorphic DNA reaction(RAPD) depending on (4) random primers, and the results showed:
... Show MoreParkinson’s disease (PD) consider as a progressive ageing neurodegenerative disease, Parkinson’s consider as a heterogenous disease, with mainly initiate through correlation between genetic and epigenetic by inducing of different factors on some related genes, these factors like (environmental, toxicants, nutrition, heavy metals, pesticides, some drugs) and also(trauma on head ,strokes) in addition to unknown reasons which cause an idiopathic PD .Current study aims to focusing on specific related PD gene called SNCA by single nucleotides polymorphism (rs2619363) as a risk factor for PD initiation disease in PD patients in addition to study the effect of polymorphisms on random Iraqi patients with different gastrointestinal
... Show MoreSalmonellosis in poultry is one of the most significant bacterial infections causing mortality, reduced production, and serious economic losses. This study aimed to study the molecular diversity among Salmonella isolates and investigate the epidemiological spread of these bacteria in broiler and layer chicken flocks in five different farms in Karbala, Iraq, using random amplified polymorphic DNA (RAPD) polymerase chain reaction (PCR). In total, 217 cloac a swabs were collected from the farms, out of which 129 and 88 swabs were taken from broiler and layer chickens. The samples were screened by PCR for S. enterica subsp. enterica using primers specific for the invA gene. Afterward, RAPD-PCR with uniplex or multiplex octamer primers was appli
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
Some genetic factors are not only involved in some autoimmune diseases but also interfere with their treatment, Such as Crohn's disease (CD), Rheumatoid Arthritis (RA), ankylosing spondylitis (AS), and psoriasis (PS). Tumor Necrosis Factor (TNF) is a most important pro-inflammatory cytokine, which has been recognized as a main factor that participates in the pathogenesis and development of autoimmune disorders. Therefore, TNF could be a prospective target for treating these disorders, and many anti-TNF were developed to treat these disorders. Although the high efficacy of many anti-TNF biologic medications, the Patients' clinical responses to the autoimmune treatment showed significant heterogeneity. Two types of TNF receptor (TNFR); 1 an
... Show MoreThe increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion
... Show MoreIn this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.
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Breast cancer is one of the most common cancers in females. In Iraq there are noticeable elevation in incidence rates and prevalence of advanced stages of breast cancer. Ferritin is intracellular iron storage protein abundant in circulation and its main application in differential diagnosis of anemia.
The level of serum ferritin was found raised in various cancers including breast cancer. The aim of this study was to assess whether the serum ferritin concentration would be altered in Iraqi women with breast cancer and it could be related to progression of disease.
Sixty eight females participated in this study. The mean age of these females was 53.25± 9.52 .The level of serum ferritin was measured in 24
... Show MoreBackground:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th
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