Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

An essential element in English as a foreign language (EFL) learning is vocabulary. There is a big emphasis on learning the new words' meaning from the books or inside classrooms. Also, it is a major part of language teaching as well as being fundamental to the learner but there is a big challenge in vocabulary instruction due to the weak confidence by teachers in selecting the suitable practice in teaching vocabulary or they sometimes unable to specify a suitable time for it during the teaching process. The major aim of this study is to investigate the value of posters in vocabulary learning on the 2nd grade students at Halemat Alsaadia High School in Baghdad – Iraq. It hypothesized that there are no statistically significant differences

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

The research is summarized in the construction of a mathematical model using the most common methods in the science of Operations Research, which are the models of transportation and linear programming to find the best solution to the problem of the high cost of hajj in Iraq, and this is done by reaching the optimum number of pilgrims traveling through both land ports and the number Ideal for passengers traveling through airports by Iraqi Airways, instead of relying on the personal experience of the decision-maker in Hajj and Umrah Authority by identifying the best port for pilgrim's travel, which can tolerate right or wrong, has been based on scientific methods of Operations Research, the researcher built two mathematical models

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

The objective of this work was to study the effect of oral administration of Cyperus esculentus (CE) and its alcoholic extract on sperm function parameters in prepubertal mice as a model for human .The animals were divided into three groups each contains 6 animals .Group 1 was treated with 150 mg/ kg body weight /day of crude CE, group 2 was treated with same dose of alcohol extract of CE and group 3 regarded as control throughout six weeks period. The results showed a significant (p> 0.05) increase in the mean of sperm concentration ,sperm motility percent and progressive sperm motility between treated groups and control . There was no differences among groups in the mean of sperm normal morphology and sperm viability . No significa

The existing study aimed to assess four soil moisture sensors’ capacitive (WH51 and SKU: S EN0193) and resistive (Yl69 and IC Station) abilities, which are affordable and medium-priced for their accuracy in six common soil types in the central region of Iraq. The readings’ calibration for the soil moisture sensor devices continued through two gravimetric methods. The first depended on the protocols’ database, while the second was the traditional calibration method. The second method recorded the lowest analysis error compared with the first. The moderate-cost sensor WH51 showed the lowest standard error (SE), MAD , and RMSE and the highest R² in both methods. The performance accuracy of WH51 was close to readings shown by the manufac