This research aims to identify how organizational compatibility, which represents the independent variable, affects higher performance, which is considered a dependent variable, given the importance of these variables in industrial organizations and their clear impact on their stability, survival, and growth in the light of changing environmental challenges.  Where the practical research problem was represented by the weakness of awareness of the importance toward organizational compatibility and its dimensions (organizational loyalty, organizational similarity, affiliation or membership, compatibility with goals, and compatibility with values), which is meant by the individual's compatibility with the organization in which he/she w

The aim of this work is to study the effect of diesel fuel percentage on the combustion processes in compression ignition engine using dual – fuel (diesel and LPG).

 The brake thermal efficiency increased with the increase of diesel fuel rate at low loads, and decreased when load increased. To get sufficient operation in engine fueled with dual fuel, it required sufficient flow rate of diesel fuel, if the engine fueled with insufficient diesel fuel erratic operation with miss fire cycles presented.

Dual-fuel operation at part load showed higher specific fuel consumption than straight diesl operation. At full loads, brake specific fuel consumption of duel fuel engine approaches that for diesel fuel values.

The research aims to shed light on banking liberalization and explain its impact on attracting customers, especially since Iraq adopted this policy after (2003) due to the changes that occurred, as the Central Bank of Iraq granted flexibility to banks in setting the interest rate on deposits and loans as well as allowing the entry of foreign banks in the local environment. The research relied on the analytical method for the dimensions of banking liberalization represented by (liberating interest rates, liberating credit, legal reserve requirements, entering foreign banks, privatization) as well as the factors affecting the attraction of customers, and a number of Iraqi banks listed in the Iraqi Stock Exchange were selected as a

Gypsiferous soil deposits (Gypcrete) are weakly consolidate earthy mixture of secondary gypsum, sand and clay. It is formed in arid and semi- arid area with annual precipitation rainfall less than 400mm. These sediments occur in surface and subsurface in region of little rainfall and rapid evaporation. This research deals with the study of gypcrete in Alexandria to improve the mineralogical and geochemical properties of the gypcrete. The gypcrete soil is used as raw material to produce the plaster for building purposes. Three samples of gypcrete were chemically and geochemically analyzed. The common mineral is howed in 0-0.5m Gypsum followed by Calcite in 0-1m and Quartz in 1-1.5m due to leaching and infiltration by rainfall as well as it

The current study aims to assess zooplankton diversity in Bahr Al-Najaf depression using diversity index, specimens were collected from five sites at Bahr Al-Najaf depression, Iraq during April 2017 to March 2018.

Forty-eight taxa of zooplankton were identified including 26 taxa to Copepoda, 17 taxa belonged to Rotifers and 5 taxa to Cladocera: Copepoda was the most dominant group (54.2%); Rotifera comprised (35.4%); Cladocera comprised (10.4%).

Relative abundance index of zooplankton showed Copepodite and nauplii of Harpacticoid, Hexarthra mira, Daphnia sp., Harpacticoid sp., and Copepodite and nauplii of Cyclops were more abundant. According to the constancy index

In this paper, we describe the cases of marriage and divorce in the city of Baghdad on both sides of Rusafa and Karkh, we collected the data in this research from the Supreme Judicial Council and used the cubic spline interpolation method to estimate the function that passing through given points as well as the extrapolation method which was applied for estimating the cases of marriage and divorce for the next year and comparison between Rusafa and Karkh by using the MATLAB program.

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This