Iraq is a developing country with a high population. In Iraq, heavy metal and metalloid contamination has resulted from both industrialisation and environmental sources, providing serious health risks to the local population. We conducted one of the most comprehensive analyses on the current state of Iraq's heavy metal and metalloid pollution in this paper, which included water, soil, paddy, and rice. A study was carried out to determine the concentration of heavy metals including Lead (Pb), Cadmium (Cd), Iron (Fe), manganese (Mn), Cobalt (Co), Magnesium (Mg), Aluminum (Al), and Copper (Cu) of 39 irrigation water samples, 75 soil samples, 75 paddy samples, and 75 rice samples in two Iraqi governorates (Diyala , and Salah al-Din ). Samples were taken from three fields in each province.. Atomic Absorption Spectrophotometer was used to determine heavy metals concentrations. Iraqi Quality Standardization (IQS (and World Health Organization (WHO) were considered as the permissible limits. The results showed that all irrigation water samples were exceeded the permissible limit for Pb, Cd, Fe, and Mn metals, while all soil samples were exceeded for Mn and Mg metals. Paddy and rice samples were exceeded for only Pb metal permissible limit, which was high, for example, Pb metal concentrations of rice and paddy ranged from 1.805-4.776 mg/kg, 0.642-3.481 mg/kg respectively, while the permissible limit was 0.2 mg/kg. Consequently, rice samples were deemed unfit for human consumption, with the contamination coming from irrigation water. therefore, this paper has suggested that the Irrigation water treatment should be strongly advised and evaluated.
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
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
... Show MoreIn this paper, we investigate the impact of fear on a food chain mathematical model with prey refuge and harvesting. The prey species reproduces by to the law of logistic growth. The model is adapted from version of the Holling type-II prey-first predator and Lotka-Volterra for first predator-second predator model. The conditions, have been examined that assurance the existence of equilibrium points. Uniqueness and boundedness of the solution of the system have been achieve. The local and global dynamical behaviors are discussed and analyzed. In the end, numerical simulations are confirmed the theoretical results that obtained and to display the effectiveness of varying each parameter
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
... Show More'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal
A pap test is a simple technique which can detect pre-cancerous and cancerous cells in the vagina and cervix. Cervical cancer is the easiest gynecologic cancer we could prevent it, with regular screening tests and follow-up this screening may avoid cervical cancer or detact it early.This study aims to estimate cytological changes and precancerus lesions during Pap smear test and visual inspection of the cervix on Iraqi women and determine the relationship with demographic characteristics. The study included 50 women aged 18-56 years (mean 39 ±10) in National Cancer of Research Center (NCRC) belong to Baghdad University. These women suffered from genital problems or
... Show MoreIn this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr2O3) with Titanium dioxide (TiO2) nanofibers (Cr2O3-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO2 exhibits nanofibers (TNFs) shape struct
... Show MoreIn 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.
This article showcases the development and utilization of a side-polished fiber optic sensor that can identify altered refractive index levels within a glucose solution through the investigation of the surface Plasmon resonance (SPR) effect. The aim was to enhance efficiency by means of the placement of a 50 nm-thick layer of gold at the D-shape fiber sensing area. The detector was fabricated by utilizing a silica optical fiber (SOF), which underwent a cladding stripping process that resulted in three distinct lengths, followed by a polishing method to remove a portion of the fiber diameter and produce a cross-sectional D-shape. During experimentation with glucose solution, the side-polished fiber optic sensor revealed an adept detection
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