Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

he present work, among other previous studies done in our lab, aimed to highlight the histopathological effect of S. xylosus peptidoglycan in comparison to LPS of E. coli. Materials and methods: One hundred and fifty urine specimens were collected from urinary tract infection patients visiting Baghdad hospitals. The histopathological effects of S. xylosus S24 peptidoglycan was studied in the urinary tract of female mice by injecting 5 animal groups at the following concentrations: 1000, 2000, 3000, 4000, and 5000 µg/mL. Another 5 groups were injected with 10, 25, 50, 75, and 100 ng/mL of E. coli (serotype 0128:B12) LPS. Results: Ten isolates were confirmed to be Staphylococcus xylosus. Histopathological study showed different pathological

The study aimed to identify the E-leadership practice at Princess Nora Bint Abdul Rahman University and to explore the obstacles that are facing the leaders in the implementation of E-leadership, in addition to find mechanisms to improve the practice of electronic driving at the university in light of the Corona pandemic. A descriptive analytical approach was used by depending on a questionnaire to collect the needed data. The study sample consisted of (139) heads of departments, attorneys' colleges and support Deanships universities. The study results showed that E-leadership employment recorded a medium to high degree. Especially at university, that publishing decisions electronically and uses technical means in providing its services.

This study was designed to compare the effect of two types of viral hepatitis A and E (HAV
and HEV) on liver functions in Iraqi individuals by the measurement of biochemical changes
associated with hepatitis.
The study performed on 58 HEV and 66 HAV infected patients compared with 28 healthy
subjects. The measured biochemical tests include total serum bilirubin, serum transminases (ALT
and AST) alkaline phosphatase (ALP) and gamma glutamyl transferase (GGT).
The study showed that adolescent and young adults (17-29) years, were mostly affected by
HEV while children (5-12) years were frequently affected by HAV. The severity of liver damage in
HEV patients was higher than HAV patients as a result of high serum transa

One hundred twelve urine samples were collected from Baghdad hospitals and examined by different identification techniques. Seventy isolates (62.5%) were diagnosed as Escherichia coli after microscopic and cultural identifications. The result of PCR product electrophoresis on the isolates showed that thirteen isolates (18.57%) have Pap E gene which are uropathogenic E. coli. Antibiotic susceptibility test was done, and four high resistant strains were mixed with aqueous extract of Quercus infectoria plant in 96 well ELISA plate and incubated for different times. After 0, 6, and 12 hr. of incubation, the effect of the plant extract on the bacterial growth was determined by ELISA reader, and the effect on the expression of P