Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

This study is carried out to investigate the prevalence of Coxiella burnetii (C. burnetii) infections in cattle using an enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) assay targeting IS1111A transposase gene. A total of 130 lactating cows were randomly selected from different areas in Wasit province, Iraq and subjected to blood and milk sampling during the period extended between November 2018 and May 2019. ELISA and PCR tests revealed that 16.15% and 10% of the animals studied were respectively positive. Significant correlations (P<0.05) were detected between the positive results and clinical data. Two positive PCR products were analyzed phylogenetically, named as C. burnetii IQ-No.5 and C. burnet

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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

Autism 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

Praise be to God, Lord of the Worlds, and prayers and peace be upon the Master of Messengers and his family and companions.

The study of the jurisprudential opinions of scholars, their choices, or their weightings, sheds light on the approach they followed in their choices, and reveals the originality of the scholar or his influence on those who preceded him from among the scholars.

And the commentators of the noble hadith of the Prophet have their important contributions in this aspect, as they undertake the task of explaining the noble hadith, the second source of legislation

Contemporary commentators have their share in the service of the honorable hadith, and the statement of their choices and preferences, and am

Praise be to Allah, the Lord of the Worlds, the best prayer and the best prayer, on our master Muhammad, and on his pure God, and his companions and the faithful, and who followed them by charity to the day of religion. This relationship between emphasis, is a sincere, and this harmony, such as the relationship between water, and the green, but it is good, but, with greenery, it is better, and as well as alone, is a beautiful view, but the most beautiful, with the most beautiful. From here he was starting on myself in writing the fundamentalist research of jurisprudence, to show the depth of this interconnection. The doctrine as a new term, then the taj al-Din al-Suobki came after three centuries, and a

This research is drawn from a doctoral dissertation, studying the approach of Sheikh Abd al-Qadir al-Muhajir al-Sanandji al-Kurdi (1303 AH) on the issue of proving the existence of God Almighty.
Sheikh Abd al-Qadir al-Sanandji was one of the scholars well versed in mental sciences. He has many books, all of them in the sciences of speech and wisdom, and among his books is the book (Raising the Eyebrow in Explanation of Ithbat al-Wajib), which is still a manuscript that has not been printed.
Through this book, the researcher studied the evidence of Sheikh Abdul Qadir to prove the existence of God Almighty, and compared it with the evidence of philosophers and theologians.
At the beginning, he presented a study on the import