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

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

A new azo dye, 5,5-[1,2-phenylenebis(2,1-biazenediyl)]bis[8-quinolino], was synthesized by reacting the diazonium salt of o-phenylenediamine with 8-hydroxyquinoline. The ligand was subsequently used to prepare a series of metal complexes with V(IV), Fe(III), Cr(III), Mn(II), Mo(VI), and Ru(III). The ligand was characterized using 1H and 3C-NMR spectroscopy, while the metal complexes were analyzed using UV-Vis, FT-IR, and mass spectrometry, along with thermal analysis (TGA, DSC), (C.H.N.), conductivity measurements, magnetic susceptibility, and metal and chlorine content analysis, the results indicated that the ligand exhibits tetracoordination. The complexes predominantly formed octahedral geometries, except for the vanadium complex, which

Objective: Schiff’s and Mannich bases of isatins are an important group of heterocyclic compounds which are of great importance in medicinal chemistry as antimicrobial agents. In the vision of these facts, new bis-Schiff bases and Mannich bases of isatins were synthesized. Methods: Three different bis-Schiff bases (3a-c) have been synthesized by reacting isatin, 5-fluoroisatin and 5-methoxy isatin with thiophene-2- carboxaldehyde using hydrazine hydrate to link between the carbonyl compounds, and then these bis- Schiff bases were condensed with two different secondary amines (piperidine and morpholine) separately, and formaldehyde to form the Mannich bases (4a-c and 5a-f), respectively. Results: The structures of the newly synthesized com

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

Many of the elementary transformations of determinants which are used in their evaluation and in the solution of linear equations may by expressed in the notation of matrices. In this paper, some new interesting formulas of special matrices are introduced and proved that the determinants of these special matrices have the values zero. All formulation has been coded in MATLAB 7.