The Al-Kindy College Medical Journal (KCMJ) is an Iraqi scholarly journal published by the Al-Kindy College of Medicine, University of Baghdad. It was officially founded in 2004. It is a peer-reviewed journal, published in both online and printed forms. It has a mission to offer a publication platform that mirrors recent knowledge and findings in the field of medicine and medical sciences. It publishes various types of articles, including editorial, review article, research article, brief report, case report, and letter to editor. It accepts articles in the English language. It was biannually published till 2021 when it started to launch three issues per year. The journal is registered with numerous partners, including Iraqi Academi

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

A batch adsorption system was applied to study the adsorption of methylene blue from aqueous solution by Iraqi bentonite and treated bentonite with different amount of zinc oxide (ZnO). The adsorption capacities of methylene blue onto bentonite were evaluated. The equilibrium between liquid and solid phase was described by Langmuir model better than the Freundlich model. Langmuir and Freundlich constants have been determined. The separation factor or equilibrium parameter, RL which is used to predict if an adsorption system is favourable or unfavourable was calculated for all cases.

The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

Biomass is a popular renewable carbon source because it has a lot of potential as a substitute for scarce fossil fuels and has been used to make essential compounds like 5-hydroxymethylfurfural (HMF). One of the main components of biomass, glucose, has been extensively studied as a precursor for the production of HMF. Several efforts have been made to find efficient and repeatable procedures for the synthesis of HMF, a chemical platform used in the manufacturing of fuels and other high-value compounds. Sulfonated graphite (SG) was produced from spent dry batteries and utilized as a catalyst to convert glucose to 5-hydroxymethylfurfural (HMF). Temperature, reaction time, and catalyst loading were the variables studied. When dimethyl sulfo