In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

The design, synthesis, and characterization of a star shaped 2,4,6-tris-(4`-carboxyphenoxy)-1,3,5-triazine liquid crystalline with columnar discotic mesophase properties establish H-bond interactions with 3,5-dialkoxypyidine were reported. The structures of the synthesized compounds were actually determined by elementary analysis, and FT-IR, ¹HNMR, ¹³CNMR, and mass spectroscopy. The mesomorphic properties of these mesogens were examined using differential scanning calorimetry (DSC) and optical polarizing microscopy (OPM). The synthesized molecules exhibited enantiotropic hexagonal columnar liquid crystal, which depends for the H- bond complex in a 1:3 ratio.

Aim: To find any association between specific ABO blood groups and FUT2 secretory status and COVID-19 in a sample of Iraqi dentists. Materials and Methods: For each participant, a questionnaire including demography, COVID-19 status, blood grouping, and RH factor, with chemo-sensitive symptoms was recorded. The saliva samples were collected and DNA was extracted from leukocytes. Sequencing of molecular detection of the FUT2 gene by real-time PCR and the data was done, whilst drawing the phylogenetic tree. Results: Out of 133, most of the dentists were female 61%, most were just under 35 years of age. The most participants in this study were predominantly with blood group O (40%), followed by B, A, and AB, with (90%) of them were RH+.

 The current paper studied the concept of right n-derivation satisfying certified conditions on semigroup ideals of near-rings and some related properties. Interesting results have been reached, the most prominent of which are the following: Let M be a 3-prime left near-ring and A_1,A_2,…,A_n are nonzero semigroup ideals of M, if d is a right n-derivation of M satisfies on of the following conditions,
d(u_1,u_2,…,(u_j,v_j ),…,u_n )=0 ∀ 〖 u〗_1 〖ϵA〗_1 ,u_2 〖ϵA〗_2,…,u_j,v_j ϵ A_j,…,〖u_n ϵA〗_u;
d((u_1,v_1 ),(u_2,v_2 ),…,(u_j,v_j ),…,(u_n,v_n ))=0 ∀u_1,v_1 〖ϵA〗_1,u_2,v_2 〖ϵA〗_2,…,u_j,v_j ϵ A_j,…,〖u_n,v_n ϵA〗_u ;
d((u_1,v_1 ),(u_2,v_2 ),…,(u_j,v_j ),…,(u_n,v_n ))=(u_

Objective(s): The aim of the study was to identify the prevalence of overweight and obesity in adolescence and
to estimate the effect of socio- demographic and health behaviors that predicting obesity in adolescents.
Methodology: A cross-sectional descriptive study was being carried out at three public Arabic secondary
schools in Erbil city from October 1
st 2010 to January 30th 2011. A systematic randomly sample size of 461 students
was selected.
Results: In this study, the age of (46.2%, 122) of males students were ranged between (17- 18.9) years old compared
to females students (74.1%, 146) their age ranged between (15 -16.9) years old. About (3.4%, 9) of males
adolescents having overweight while all female ado

Diabetes imposes a substantial public health burden; according to the International Diabetes Federation, there were about 3.4 million diabetes related deaths worldwide in 2024, and in Iraq, the Federation reports that one in nine adults lives with diabetes in 2024, with 14,683 adult deaths attributable to diabetes and a total diabetes related health expenditure of 2,078 million United States dollars. The dataset analyzed in this study contains 1,000 records collected in 2020 from two Iraqi teaching hospitals and includes multiple clinical and laboratory measurements with three outcome classes, namely Non diabetic, Pre diabetic, and Diabetic, with a low prevalence of the Pre diabetic class and an imbalanced overall class distribution; the da

Copper is a cheaper alternative to various noble metals with a range of potential applications in the field of nanoscience and nanotechnology. However, copper nanoparticles have major limitations, which include rapid oxidation on exposure to air. Therefore, alternative pathways have been developed to synthesize metal nanoparticles in the presence of polymers and surfactants as stabilizers, and to form coatings on the surface of nanoparticles. These surfactants and polymeric ligands are made from petrochemicals which are non- renewable. As fossil resources are limited, finding renewable and biodegradable alternative is promising.The study aimed at preparing, characterizing and evaluating the antibacterial properties of copper nanoparticle

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c