Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

In this study, an unknown force function dependent on the space in the wave equation is investigated. Numerically wave equation splitting in two parts, part one using the finite-difference method (FDM). Part two using separating variables method. This is the continuation and changing technique for solving inverse problem part in (1,2). Instead, the boundary element method (BEM) in (1,2), the finite-difference method (FDM) has applied. Boundary data are in the role of overdetermination data. The second part of the problem is inverse and ill-posed, since small errors in the extra boundary data cause errors in the force solution. Zeroth order of Tikhonov regularization, and several parameters of regularization are employed to decrease error

A cut-off low is a closed low with a low value of geopotential height at the upper atmospheric levels that has been fully detached (cut-off) from the westerly flow and move independently. A cut-off low causes extreme rainfall events in the mid-latitudes regions. The main aim of this paper is to investigate the cut-off low at 500 hPa over Iraq from a synoptic point of view and the behavior of geopotential height at 500 hPa. To examine the association of the cut-off low at 500 hPa with rainfall events across Iraq, two case studies of heavy rainfall events from different times were conducted. The results showed that the cut-off low at 500 hPa with a low value of geopotential height will strengthen the low-pressure system at the surface, lea

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

In this article, a new deterministic primality test for Mersenne primes is presented. It also includes a comparative study between well-known primality tests in order to identify the best test. Moreover, new modifications are suggested in order to eliminate pseudoprimes. The study covers random primes such as Mersenne primes and Proth primes. Finally, these tests are arranged from the best to the worst according to strength, speed, and effectiveness based on the results obtained through programs prepared and operated by Mathematica, and the results are presented through tables and graphs.

In this work various correlation methods were employed to investigate the annual cross-correlation patterns among three different ionospheric parameters: Optimum Working Frequency (OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF). The annual predicted dataset for these parameters were generated using VOCAP and ASASPS models based on the monthly Sunspot Numbers (SSN) during two years of solar cycle 24, minimum 2009 and maximum 2014. The investigation was conducted for Thirty-two different transmitter/receiver stations distributed over Middle East. The locations were selected based on the geodesic parameters which were calculated for different path lengths (500, 1000, 1500, and 2000) km and bearings (N, NE, E, S

Understanding breaking news necessitates a special attention, since they are written with a special style. The study aims at identifying the difficulties faced by the Iraqi university EFL learners in comprehending English breaking news. The study included 10 fourth year students enrolled at the Department of English, College of Education for Humanities, University of Anbar. Thus, a questionnaire as a research instrument, was sent online to the students. The questionnaire points were related to the identification of difficulties faced by the learners in comprehending English breaking news. The data of the study were (10) headlines selected purposively from Euronews website. The data were qualitatively analyzed based on quantifying the qua

Methicillin resistant Staphylococcus aureus (MRSA) is one of the principal nosocomial causative agents. This bacterium has the capability to resist wide range of antibiotics and it is responsible for many diseases like skin, nose and wounds infection. In this study, randomly amplified polymorphic DNA (RAPD)-PCR was applied with ten random primers to examine the molecular diversity among methicillin resistant Staphylococcus aureus (MRSA) isolates in the hospitals and to investigate the genetic distance between them. 90 Isolates were collected from clinical specimens from Iraqi hospitals for a total of 90 isolates. Only 10 strains (11.11%) were found to be MRSA. From these 10 primers, only 9 gave clear amplification products. 91 fragment l