We propose a system to detect human faces in color images type BMP by using two methods RGB and YCbCr to determine which is the best one to be used, also determine the effect of applying Low pass filter, Contrast and Brightness on the image. In face detection we try to find the forehead from the binary image by scanning of the image that starts in the middle of the image then precedes by finding the continuous white pixel after continuous black pixel and the maximum width of the white pixel by scanning left and right vertically(sampled w) if the new width is half the previous one the scanning stops.
Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
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
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreThe aim of the research is to identify the values of the level of muscular strength of the thighs, as well as to identify the significance of the differences between the pre-tests and the post-tests for the first-class football referees in the Iraqi Premier League. The researchers used the one-group experimental approach for its suitability to the nature of the study problem, and the research sample was from first-class referees in the Iraqi Premier League for the sports season (2022/2023), and their number was (15) referees. They took the comprehensive enumeration method, and special tests were conducted on them in the stadium and the private hall at the Ministry of Youth and Sports Center. After analyzing and discussing the result
... Show MoreThe aim of this study was to measure the effectiveness of a proposed program to develop the creative abilities of the students of Tabuk University and its impact on the creative output of the NEOM project. The sample of the study consisted of (50) university students divided into two groups: an experimental group of 25 students who receive the proposed training program, and control group of (25) students.
To achieve these objectives, the researcher designed and developed tools to collect the required data, which were verified their validity and reliability.
The descriptive statistics of mean, standard deviations, correlation coefficient, T test for the associated sample were used in the analysis of the results of th
... Show MoreAutorías: Imad Kadhim Khlaif, Israa Gameel Hussein, Talib Faissal Shnawa. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 5, 2022. Artículo de Revista en Dialnet.
The event of crossing the barriers is one of the Power Games activities that have received great attention in the field of researches. Which led to ma..
This study was included preparing acold aqueous extract of clove buds The study also comprised the isolation and studying the proteinous compound,which was seperated using gel filtration technique and determined approximately molecular weight of this isolated compound(6799) dalton . The aim of the study demonstrate effects of the crude aqueous, non proteinous extract, proteinous precipitate and proteinous compound on serum glucose, total cholesterol, triglyceride and high density lipoprotein-cholesterol levels, also glutathione and malondialdehyde levels in liver and kidney tissues in diabetic mice-induced alloxan.Extracts were administerated interaperitioneally. The results were indicated that the crude aqueous, non proteinous extr
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That Iraq's dependence on the revenues of the oil product in financing its development programs and growth rates , Making the economy affected by external forces represented by fluctuations in crude oil prices in the global market, Which is directly reflected on the performance and efficiency of the Iraqi economy.
The study adopted its objectives to analyze the time series for the period (1988 - 2015) through the use of standard and statistical methods, Four standard models were estimated to reach those targets, Where the results of the stability test showed instability of most variables at their original level, But to achieve stability when taking the first differences, While the result
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