The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

The paper is concerned with the state and proof of the solvability theorem of unique state vector solution (SVS) of triple nonlinear hyperbolic boundary value problem (TNLHBVP), via utilizing the Galerkin method (GAM) with the Aubin theorem (AUTH), when the boundary control vector (BCV) is known. Solvability theorem of a boundary optimal control vector (BOCV) with equality and inequality state vector constraints (EINESVC) is proved. We studied the solvability theorem of a unique solution for the adjoint triple boundary value problem (ATHBVP) associated with TNLHBVP. The directional derivation (DRD) of the "Hamiltonian"(DRDH) is deduced. Finally, the necessary theorem (necessary conditions "NCOs") and the sufficient theorem (sufficient co

     Some intestinal parasites might impact a child's nutritional condition and lipid profile. It has recently been revealed that these parasites have a link to biometric data and lipid profiles. As a result, the current study aims to see how Giardia lamblia and Cryptosporidium affect nutritional status and lipid profile. From October 2021 to March 2022, this study was done in Baghdad. The participants in the study were 110 children of both sexes, ranging in age from 2 to 17. According to the results of the stool examination, the children were separated into three groups: those infected with Giardia lamblia (n=47), those infected with Cryptosporidium (n=43), and those who appeared to be healthy (n=

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

Face recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o

Elastic magnetic M1 electron scattering form factor has been calculated for the ground state J,T=1/2-,1/2 of 13C. The single-particle model is used with harmonic oscillator wave function. The core-polarization effects are calculated in the first-order perturbation theory including excitations up to 5ħω, using the modified surface delta interaction (MSDI) as a residual interaction. No parameters are introduced in this work. The data are reasonably explained up to q~2.5fm-1 .

A special methodology for adding a watermark for colored (RGB) image is formed and adding the wavelet transform as a tool during this paper. The watermark is added into two components. The primary one is by taking the key that contain associate eight range from (0...7) every range in it determines the actual bit position in specific component of canopy image. If that bit is analogous to the bit in watermark, (0) are hold on within the Least Significant Bit (LSB) of the watermarked image; otherwise (1) are hold on. The other is that it will add multiple secret keys victimization shift and rotate operations. The watermark is embedded redundantly over all extracted blocks in image to extend image protection. This embedding is completed with

The current study was concerned to address these gaps in literature by identifying: first level and type of future visions among the next graduation student, second level and type of future visions among the sample according to gender (Male- Female), third level of the illegal immigration among the sample, fourth level of the illegal immigration according to gender (Male, Female), and finally the relationship between future visions and illegal immigration. To achieve the aims of the current study, the researchers created a questionnaire for the future visions. The psychometric properties (e.g. face validity, structure validity, and reliability) were tested. Base on the current sample, results showed that the questionnaire had sound psych