With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

This research investigates the engagement of the Iraqi audience with ethnographic programs and their impact on knowledge enhancement and intellectual perspectives. A questionnaire consisting of closed-ended questions was designed and administered to a purposive sample of 400 participants who exclusively follow ethnographic programs and documentary channels. The data were transcribed and subjected to statistical analysis using the SPSS software to ensure reliability and test hypotheses. The findings revealed that Al Jazeera Documentary Channel had the highest viewership percentage among respondents for ethnographic programs, while DW (Deutsche Welle) had the lowest viewership percentage. This suggests that Al Jazee

The Bangestan reservoir, which occurs in the Ahwaz oilfield, consists of the middle Cretaceous limestone Ilam and Sarvak Formations that were deposited in the Zagros Basin. The reservoir is divided into ten Zones (A to J) formed in the upper Albian-Santonian and contains considerable hydrocarbon accumulations. The limestones were deposited on an extensive shallow carbonate platform on a passive margin and are dominated by rudist biostrome and grainstone facies. Paleogeographical changes mean that identification of the facies is complex. Seismic stratigraphy and isotopic data are used to better understand the structural and geological setting and develop an understanding of the sedimentary environment. The results show that the rudist biostr

Mishrif Formation was deposited during The Cenomanian-Early Turonian, which has been studied in selected Tuba and Zubair OilFields, these wells (TU-5, TU-24, TU-40, ZB-41, ZB-42, and ZB-46) are located within Mesopotamian basin at southern Iraq and considered as a major carbonate reservoir in Iraq and the Arabian Gulf. The palaeontological investigations mainly depending on benthonic foraminifera of the studied wells of Tuba and Zubair Oilfields in Mishrif Formation, twenty-four species belonging to fourteen genera are recognized of benthonic foraminifera, which has been recognized through this study, especially benthonic foraminiferal, indicating four zones as follows:

The performance of a synergistic combination of electrocoagulation (EC) and electro-oxidation (EO) for oilfield wastewater treatment has been studied. The effect of operative variables such as current density, pH, and electrolyte concentration on the reduction of chemical oxygen demand (COD) was studied and optimized based on Response Surface Methodology (RSM). The results showed that the current density had the highest impact on the COD removal with a contribution of 64.07% while pH, NaCl addition and other interactions affects account for only 34.67%. The optimized operating parameters were a current density of 26.77 mA/cm2 and a pH of 7.6 with no addition of NaCl which results in a COD removal efficiency of 93.43% and a specific energy c

Moisture-induced damage is one of the primary causes of premature distress in asphalt pavements, leading to reduced service life and increased maintenance costs. Although nanomaterials have shown potential in enhancing asphalt performance, the underlying composite interaction mechanisms among nanomaterials, asphalt binder, and aggregate phases under moisture exposure are still not fully understood. In addition, comparative evaluations under consistent experimental conditions remain limited. This study investigates the influence of five nanomaterials: nano-silica (NS), nano-alumina (NA), nano-titanium dioxide (NT), nano-zinc oxide (NZ), and carbon nanotubes (CNT) on the physical and mechanical properties of asphalt binders and mixtur