Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This study addresses quantum computers as one of the most significant contemporary technological transformations that promise to reshape the future of global computing. It aims to clarify the conceptual foundations of quantum computing and to identify the fundamental differences between quantum and classical computers in terms of processing mechanisms, computational speed, and the ability to solve highly complex problems. The study focuses on key concepts such as the qubit, superposition, and entanglement, highlighting their role in enabling computational capabilities that exceed the limits of classical computing. It also discusses the future applications of quantum computers in areas such as cryptography, artificial intelligence, big data

We described herein the synthesized and characterized of new bent and liner core compounds containing thiazolidin-4-one ring[XI-XIII] and [XIV-XVI] respectively. These compounds synthesized by sequence reactions starting from reaction resorcinol or hydroquinone with chloracetyl chloride to yield compounds [I] and [II] ,then the later compounds reactant with 4-hydroxybenzylaldehyde to product dialdehyde compounds [III] and [IV] .The Schiff bases compounds[V-VII] and [VIII-X] synthesized from reaction the compound [III] or [IV] with different aromatic amines, while the bent and liner core mesogens containing thiazolidin-4-one ring [XI-XIII] and [XIV-XVI] synthesized from reaction Schiff bases compounds[V-VII] or [VIII-X] with thioglycolic aci

This study outlines the synthesis of substituted 1,2,4-triazole derivatives through the cyclization reaction of thiourea derivatives. The process begins with the reaction of different halides with KSCN to produce isothiocyanate derivatives. then followed by a reaction with isonicotinic acid hydrazide to yield thioureas (1-6), with a yield rate of (72-88%). Then, compounds (1-6) were treated with alkaline medium 4 N (NaOH) to produced 1,2,4-triazole derivatives (7-12) with a yield (51-69%).The structure of the prepared compounds was characterized using FTIR,1HNMR and 13CNMR spectroscopy. Some of the synthesized compounds were tested for antimicrobial activity when, compound 9 showed strong activity against gram positive bacteria (Sta

A new series of Schiff bases compounds , containing an azomethine linkage was synthesized and expected to be biologically active .The structures of these compounds were identified by IR , Uv/vis spectra , melting points and followed by T.L.C.The biological activity of these compounds was studied

Objective: This study involved the synthesis of new Schiff bases and 1,3-oxazepine derivatives from the baclofen drug and study the anticancer activities. Methods: Baclofen was initially reacted with aromatic aldehydes to create Schiff base derivatives (Ia–Ib), which were then closed in the next step using anhydrous acids to form oxazepine derivatives (IIa–IId). Results: The title compounds were synthesized successfully and identified using FT-IR, 1H NMR, and 13C NMR spectroscopy. Additionally, compound (IIc)’s (3-(4-chloro-phenyl)-4-[2-(4nitro-phenyl)-4,7-dioxo-4,7-dihydro-[1,3] oxazepin-3-yl]butyric acid) anticancer activity was assessed using MTT assay against FTC-133 (thyroid cancer) compared with WRL-68 (normal cell line). Discus

The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

KE Sharquie, SA Al-Mashhadani, AA Noaimi, AA Hasan, Journal of Cutaneous and Aesthetic Surgery, 2012 - Cited by 19