The virulent genes are the key players in the ability of the bacterium to cause disease. The products of such genes that facilitate the successful colonization and survival of the bacterium in or cause damage to the host are pathogenicity determinants. This study aimed to investigate the prevalence of virulence factors (esp, agg, gelE, CylA) in E. faecalis isolated from diverse human clinical collected in Iraqi patient , as well as to assess their ability to form biofilm and to determine their haemolytic and gelatinase activities. Thirty-two isolates of bacteria Enterococcus faecalis were obtained, including 15 isolates (46.87%) of the urine, 6 isolates (18.75%) for each of the stool and uterine secretions, and 5 isolates (15.62%) of the wounds from various hospitals in Baghdad, including (Central Children's Hospital, Educational Laboratories, Ibn Al-Baladi Hospital).The isolates were confirmed to belong to the genus E.faecalis after performing morphological and biochemical microscopic examinations and for final diagnosis using the VITEC 2 system. The virulence genes viz. cylA, esp, gelE and agg were recognized in the E. faecalis, and the consequences appeared that the bacteria had eps gene in 32 isolates (100%). As for the agg gene, 32 isolates (100%) were carriers of this gene, which was responsible for these isolates' aptitude to form the biofilm. While for the gelE gene, 27 isolates (84.37%) of the isolates carried this gene, responsible for gelatinase activity whereas, the gene responsible for hemolysis cyl, there were 29 isolates (90.62%) of the total isolates. The presemce of genes in the isolates would be helpful to determine the colonization and survival of the bacterium in or causing damage to the host.
Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
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Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them. This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c
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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
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The 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
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Abstract
On 11/1/2008 amounts of snows fell on various sections of Iraq, one of
which is Baghdad. The analysis process of climatic maps proved that the
advance trough of Sudanese depression towards the city is the reason behind
the formation of this weather state supported by could trough in the (500) mb
pressure level. .
The research concluded that the phenomenon of global warming
witnessed by the world recently had a main role in the occurrence of this
phenomenon due to the raise in earth temperature as a result of evaporation
rate increase leading to an increase in water vapor and cloud formation with
high tops and low bases which form sows with high rates accumulating at high
and moderate latitudes le
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The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese
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