With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an

This paper presents a minimum delay congestion control in differentiated Service communication networks. The premium and ordinary passage services based fluid flow theory is used to build the suggested structure in high efficient manage. The established system is capable to adeptly manage both the physical network resource limitations and indefinite time delay related to networking system structure.

OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for ad

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

Antimicrobial resistance is one of the most significant threats to public health worldwide. As opposed to using traditional antibiotics, which are effective against diseases that are multidrug-resistant, it is vital to concentrate on the most innovative antibacterial compounds. These innate bacterial arsenals under the term «bacteriocins» refer to low-molecularweight, heat-stable, membrane-active, proteolytically degradable, and pore-forming cationic peptides. Due to their ability to attack bacteria, viruses, fungi, and biofilm, bacteriocins appear to be the most promising, currently accessible alternative for addressing the antimicrobial resistance (AMR) problem and minimizing the negative effects of antibiotics on the host’s m

Based on a finite element analysis using Matlab coding, eigenvalue problem has been formulated and solved for the buckling analysis of non-prismatic columns. Different numbers of elements per column length have been used to assess the rate of convergence for the model. Then the proposed model has been used to determine the critical buckling load factor () for the idealized supported columns based on the comparison of their buckling loads with the corresponding hinge supported columns . Finally in this study the critical buckling factor () under end force (P) increases by about 3.71% with the tapered ratio increment of 10% for different end supported columns and the relationship between normalized critical load and slenderness ratio was g

DNA methylation is one of the main epigenetic mechanisms in cancer development and progression. Aberrant DNA methylation of CpG islands within promoter regions contributes to the dysregulation of various tumor suppressors and oncogenes; this leads to the appearance of malignant features, including rapid proliferation, metastasis, stemness, and drug resistance. The discovery of two important protein families, DNA methyltransferases (DNMTs) and Ten-eleven translocation (TET) dioxygenases, respectively, which are responsible for deregulated transcription of genes that play pivotal roles in tumorigenesis, led to further understanding of DNA methylation-related pathways. But how these enzymes can target specific genes in different malignancies;