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

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

Seven fish species were collected from the drainage network at Al-Madaen region, south of
Baghdad with the aid of a cast net during the period from March to August 1993. These fishes
were infected with 22 parasite species (seven sporozoans, three ciliated protozoans, seven
monogeneans, two nematodes, one acanthocephalan and two crustaceans) and one fungus
species. Among such parasites, Chloromyxum wardi and Cystidicola sp. are reported here for
the first time in Iraq. In addition, 11 new host records are added to the list of parasites of
fishes of Iraq.

Bacterial contamination of AL-Habania reservoir was studied during the period from February 2005 to January 2006; samples were collected from four stations (AL-Warrar, AL-Theban regulator, middle of the reservoir and the fourth was towards AL-Razzaza reservoir). Coliform bacteria, faecal Coliforms, Streptococci, and faecal Streptococci were used as parameters of bacterial contamination in waters through calculating the most probable number. Highest count of Coliform bacteria (1500 cell/100ml) was recorded at AL-Razaza during August, and the lowest count was less than (300 cell/100ml) in the rest of the collection stations for all months. Fecal Coliform bacteria ranged between less than 300 cells/100ml in all stations for all months to 700 c

This research paper attempts to explore problems facing the teaching of written expression among first-year female university students. The focal point behind conducting this research is to show the importance that writing is taking as a skill in learning the language. To achieve this goal, the researcher prepared a questionnaire consisting of 20 items. The sample, whose size is 60 participants, was selected randomly from the department of Arabic, College of Education for Women, University of Baghdad. Through the use of a set of statistical means including weighting means and percentage, the findings revealed that the students face many difficulties in learning writing. The researcher suggested some recommendations, mainly improving the

Background: The autism spectrum disorder (ASD) describes a wide range of symptoms, including difficulty with social interaction and communication skills. Controversial thinking about oral health of children with ASD, in general may have a lower hygiene level than healthy individuals, low caries rate and high body weight in comparison to healthy children. This study was conducted to assess the oral health status in relation to nutritional status among institutionalized autistic children and adolescents. Materials and methods: From 12 institutes in Baghdad, the study group contained 364 child and adolescent with ASD (Male= 294, Female=70), while control group included 441 normal child and adolescent (Male=357, Female=84) from primary and seco

Gas compressibility factor or z-factor plays an important role in many engineering applications related to oil and gas exploration and production, such as gas production, gas metering, pipeline design, estimation of gas initially in place (GIIP), and ultimate recovery (UR) of gas from a reservoir. There are many z-factor correlations which are either derived from Equation of State or empirically based on certain observation through regression analysis. However, the results of the z-factor obtained from different correlations have high level of variance for the same gas sample under the same pressure and temperature. It is quite challenging to determine the most accurate correlation which provides accurate estimate for a range of pressures,

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m