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Tools for Drought Identification and Assessment: A Review

Drought is a natural phenomenon in many arid, semi-arid, or wet regions. This showed that no region worldwide is excluded from the occurrence of drought. Extreme droughts were caused by global weather warming and climate change. Therefore, it is essential to review the studies conducted on drought to use the recommendations made by the researchers on drought.  The drought was classified into meteorological, agricultural, hydrological, and economic-social. In addition, researchers described the severity of the drought by using various indices which required different input data.  The indices used by various researchers were the Joint Deficit Index (JDI), Effective Drought Index (EDI), Streamflow Drought Index (SDI), Standard Precipitation Index (SPI), Standard Evapotranspiration Index (SPEI), and Palmer Index (PI). According to the researchers in hydrology and for the most accurate description of the drought, more than one indicator for drought should be used. Most reviewed studies recommended using the Standard Precipitation Index (SPI) as the best indicator to describe the drought. 

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Publication Date
Thu Aug 25 2016
Journal Name
International Journal Of Mathematics Trends And Technology
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Publication Date
Mon Jan 01 2024
Journal Name
Applied And Computational Mathematics
Reliable computational methods for solving Jeffery-Hamel flow problem based on polynomial function spaces

In this paper reliable computational methods (RCMs) based on the monomial stan-dard polynomials have been executed to solve the problem of Jeffery-Hamel flow (JHF). In addition, convenient base functions, namely Bernoulli, Euler and Laguerre polynomials, have been used to enhance the reliability of the computational methods. Using such functions turns the problem into a set of solvable nonlinear algebraic system that MathematicaⓇ12 can solve. The JHF problem has been solved with the help of Improved Reliable Computational Methods (I-RCMs), and a review of the methods has been given. Also, published facts are used to make comparisons. As further evidence of the accuracy and dependability of the proposed methods, the maximum error remainder

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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models

The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Sat Nov 30 2019
Journal Name
Journal Of Engineering And Applied Sciences
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Publication Date
Wed Jan 01 2020
Journal Name
Medico-legal Update
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
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Publication Date
Thu Apr 01 2021
Journal Name
Neuroquantology
Finding Most Stable Isobar for Nuclides with Mass Number (165- 175) against Beta Decay

In the beta decay process, a neutron converts into a proton, or vice versa, so the atom in this process changes to a more stable isobar. Bethe-Weizsäcker used a quasi-experimental formula in the present study to find the most stable isobar for isobaric groups of mass nuclides (A=165-175). In a group of isobars, there are two methods of calculating the most stable isobar. The most stable isobar represents the lowest parabola value by calculating the binding energy value (B.E) for each nuclide in this family, and then drawing these binding energy values as a function of the atomic number (Z) in order to obtain the mass parabolas, the second method is by calculating the atomic number value of the most stable isobar (ZA). The results show

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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
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Publication Date
Fri Jun 30 2023
Journal Name
The International Tinnitus Journal
Is Topical Nasal Steroid Useful for Treatment of Otitis Media with Effusion in Children?

Background: Otitis media with effusion is a common and important pediatric clinical problem; it is the leading cause of hearing impairment in children. Medical treatment remains controversial. Aim: To evaluate the usefulness of using topical nasal steroids in the treatment of otitis media with effusion. Patients and Methods: Between November 2019 and October 2022, a prospective controlled clinical study was carried out in the department of otolaryngology at Al-Jerrahat Teaching Hospital in Medical City, Baghdad, Iraq. This study comprised 40 patients with bilateral otitis media with effusion (23 males, 17 females). Two groups were created for the patients. Patients in group A (20 patients) were treated with mometasone furoate nasal spra

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Estimation of Parameters for the Gumbel Type-I Distribution under Type-II Censoring Scheme

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

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