This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

The purpose of this research is to prepare new vanillic acid derivatives with 1,2,4-triazole-3-thiol heterocyclic ring and evaluate their antimicrobial activity in a preliminary assessment. A multistep synthesis was established for the preparation of new vanillic acid-triazole conjugates. The intermediate of 4-(4-amino-5-mercapto-4H-1,2,4-triazol-3-yl)-2-methoxyphenol (4) reacts with different heterocyclic aldehydes (thiophene-2-carboxaldehyde, pyrrole-2-carboxaldehyde, thiophene-3-carboxaldehyde, and furfural ) in ethanol containing few drops of acetic acid yielded the corresponding 4-(4-(substituted amino)-5-mercapto-4H-1,2,4-1triazol-3-yl)-2-methoxy phenol derivatives (5-8). These compounds were characterized spectroscopically by

The purpose of this research is to prepare new vanillic acid derivatives with 1,2,4-triazole-3-thiol heterocyclic ring and evaluate their antimicrobial activity in a preliminary assessment. A multistep synthesis was established for the preparation of new vanillic acid-triazole conjugates. The intermediate of 4-(4-amino-5-mercapto-4H-1,2,4-triazol-3-yl)-2-methoxyphenol (4) reacts with different heterocyclic aldehydes (thiophene-2-carboxaldehyde, pyrrole-2-carboxaldehyde, thiophene-3-carboxaldehyde, and furfural ) in ethanol containing few drops of acetic acid yielded the corresponding 4-(4-(substituted amino)-5-mercapto-4H-1,2,4-1triazol-3-yl)-2-methoxy phenol derivatives (

The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera

In this study, SnO2 nanoparticles were prepared from cost-low tin chloride (SnCl2.2H2O) and ethanol by adding ammonia solution by the sol-gel method, which is one of the lowest-cost and simplest techniques. The SnO2 nanoparticles were dried in a drying oven at a temperature of 70°C for 7 hours. After that, it burned in an oven at a temperature of 200°C for 24 hours. The structure, material, morphological, and optical properties of the synthesized SnO2 in nanoparticle sizes are studied utilizing X-ray diffraction. The Scherrer expression was used to compute nanoparticle sizes according to X-ray diffraction, and the results needed to be scrutinized more closely. The micro-strain indicates the broadening of diffraction peaks for nano