This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

This research is dealing with five sample of tomato ketchup products available in local market that were respectively as follows: Hello-Baghdad Iraq, Tiffany-Abu Dhabi, Melody-Dubai, Baidar-Saudi Arabia, and Altunsa-Turkey. Also it is dealing with four sample of sauce products available in local market that were respectively as follows: Hello-Baghdad, Iraq, Al-Badawi-Baghdad Iraq, Family-Baghdad, Iraq, and Hala-Amman Jordon. Analysis was performed on each sample three times and mean of the reading was taking. Samples were tested through terse and shorthand from lengthened steps. The spectrophotometric method used rely on theoretical and practical bases in extraction and diagnosis by UV spectrophotometer. This method in short notes, consiste

During 2011, 1900 clinical specimens (urine, wounds, burns, blood and sputum) and
240 hospital environment specimens were collected from four hospitals in
Baghdad/Medical city including: Baghdad Teaching Hospital, The Martyr Gazi Al-
Hariry Hospital, Welfare Teaching Hospital and The Burn Specialist Hospital. All
specimens were cultured and 128 Acinetobacter baumannii were obtained from
clinical and environmental specimens in a ratio of 6.05% (n=115) and 5.42%
(n=13), respectively. These isolates were identified using microscopic examination,
biochemical tests and Api 20 E system.The slide agglutination technique for rabbit
immune sera and A. baumannii bacteria was used and our data analysis revealed a
serologi

The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

Covid-19 is a respiratory disease similar to pneumonia that results from an infection with SARS-CoV-2, a recently identified virus that became a global pandemic in 2020. The severe cases of the disease show a cytokine storm, which is excessive, uncontrolled production of pro inflammatory cytokines. MicroRNA-155 is an epigenetic microRNA that has the ability to control pro-inflammatory responses in many diseases. We aim to determine the relationship between microRNA-155 expression and some cytokines (interleukin-6, interleukin-8, and interleukin-1β) in severe covid-19 cases. A case-control study of 235 samples was collected from 120 patients with severe covid-19 and 115 of mild c

    In this paper, some new types of regularity axioms, namely pairwise quasi-regular, pairwise semi-regular, pairwise pseudo regular and pairwise regular are defined and studied in both ech fuzzy soft bi-closure spaces (  bicsp’s) and their induced fuzzy soft bitopological spaces. We also study the relationships between them. We show that in all these types of axioms, the hereditary property is satisfied under closed fs bi-csubsp of . Furthermore, we define some normality axioms, namely pairwise semi-normal, pairwise pseudo normal, pairwise normal and pairwise completely normal in both  bicsp’s and their induced fuzzy soft bitopological spaces, as well as their basic properties and the relationships between them are studied.

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

Low salinity (LS) water flooding is a promising EOR method which has been examined by many experimental studies and field pilots for a variety of reservoirs and oils. This paper investigates applying LS flooding to a heavy oil. Increasing the LS water temperature improves heavy oil recovery by achieving higher sweep efficiency and improving oil mobility by lowering its viscosity. Steam flooding projects have reported many problems such as steam gravity override, but override can be lessened if the steam is is alternated with hot LS water. In this study, a series of reservoir sandstone cores were obtained from Bartlesville Sandstone (in Eastern Kansas) and aged with heavy crude oil (from the same reservoir) at 95°C for 45 days. Five reservo

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor