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

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

Abstract :

This research aims to examine the correlation and the impact of Strategic leadership on Achieving Organizational in some of establishments in ministry of construction and housing which is under public founds, Starting from the importance of research in public organizations and the importance of these organizations to the community, it is rely descriptive analytical methods in achievement of this research, the research involved board of directors, Data has collected from (92) respondents, represent the respondent society exclusively and comprehensively, it involved the general directors, assistant general directors and heads of department, The research relied programs (Excel 2010, Spss V.21), moreover, some o

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

ترك السلطان عبدالحميد الثاني بصماتهُ على أخاديد الزمان وعلى خارطة المشرق العربي الخاضع للسيطرة العثمانية أنذاك ، لكونهُ أهم شخصية أسلامية غير عربية واجهت الخطر الصهيوني ومحاولاتهم الإستيطانية في مشرق الوطن العربي ، على الرغم من صعوبة الظروف التي كانت تمر بها الدولة العثمانية داخليا ً وخارجيا ً، بما فيها من أطماع اقتسامها بين الاوربين ولذا سموها بالرجل المريض .

     The manuscript depictions of the Ilkhanate era in Iran reflect the cultural and artistic dialogue approach that prevailed in that period ,when a movement of openness to literature from different sources occurred, which led to the emergence of new features