The present research deal with ecological and geographical distribution of species and genera of Primulaceae in Iraq. The results were revealed that species distributed in the north , north-east and west of Iraq. Anagallis arvensis L. is the most prevalent species tolerant to different environmental conditions, while the species of Primula L. characterized as less widespread and limited in one District. In addition, the districts Rawanduz (MRO) and Sulaymaniyah (MSU) have ranked first in distribution of the species on geographical districts with (75%), while the districts southern desert (DSD) and Basra (LBA) in last place with (16.7%). Maps for geographical distribution for all species were illustrated.

The field efficacy of Actellic (organophosphate), Neporex (insect growth regulator) and
Ficam (carbamate), at the application rates of 2-4, 0.4-0.8 and 0.1-0.2 g AI/m2 respectively,
was studied against the larvae of Musca domestica L. Results of treatments involving horse
manure indicated that Actellic and Neporex produced sharp decrease of larval numbers (close
to zero) for 21d. But there was a slight recovery in larval numbers 14 d following treatment
with Ficam. The populations of predator mites were not affected due to insecticidal
applications.

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

Peak ground acceleration (PGA) is one of the critical factors that affect the determination of earthquake intensity. PGA is generally utilized to describe ground motion in a particular zone and is able to efficiently predict the parameters of site ground motion for the design of engineering structures. Therefore, novel models are developed to forecast PGA in the case of the Iraqi database, which utilizes the particle swarm optimization (PSO) approach. A data set of 187 historical ground-motion recordings in Iraq’s tectonic regions was used to build the explicit proposed models. The proposed PGA models relate to different seismic parameters, including the magnitude of the earthquake (Mw), average shear-wave velocity (VS30), focal depth (FD

Photoplethysmography (PPG) is a non-invasive optical technique that employs variations in light absorption produced by alteration in the blood volume in capillaries at the skin during the cardiac cycle. This study aims to understand factors related to PPG morphology; a hand-elevation, the study has modified blood flow to and from the finger was conducted in the laboratory. It is widely established that the position of the limb relative to the heart has an effect on blood flow in arteries and venous. Peripheral digital pulse wave (DPW) signals were obtained from 15 healthy volunteer participants during hand-elevation, and hand-lowering techniques wherein the right hand was lifted and lowered relative to heart level, while the left h

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

  After the internal audit as a tool of internal control in any organization, and helps in the evaluation of all internal control activities, as a tool to ensure compliance with the plans and policies to achieve the goals of the institution as much as possible of the efficiency, effectiveness, and should have the Internal Audit full independence and is linked to senior management, and aims to get the credibility and accuracy of information and data, and keep abreast of modern developments.

  The practical side includes the preparation of the questionnaire, which included a set of questions that fit the hypothesis of the research, was Tozeiha the research sample consisting of employees of the Internal Audit Department an