In the present study, gold nanoparticles (AuNPs) were prepared using a simple low cost method synthesized cold plasma at different exposure time . The nanoparticles were characterized using UV-Visible spectra, X-ray diffraction (XRD). The prepared AuNPs showed surface Plasmon resonance centered at 530, 540,and 533 nm. The XRD pattern showed that the strong intense peaks indicate crystalline nature and face centered cubic structure of gold nanoparticles for all samples were prepared .The average crystallite size of the AuNPs was 20-40 nm. Morphology of the AuNPs were carried out using FESEM. Observations show that the AuNPs synthesized we well dispersed with and particle sizes ranging from 9 to 31 nm with spherical shapes which are cle

Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

     The heterogeneity nature of carbonate reservoirs shows sever scattering of the data, therefore, one has to be cautious in using the permeability- porosity correlation for calculating permeability unless a good correlation coefficient is available. In addition, a permeability- porosity correlation technique is not enough by itself since simulation studies also require more accurate tools for reservoir description and diagnosis of flow and non-flow units. Evaluation of reservoir characterization  was conducted by this paper for Mishrif Formation in south Iraqi oil field (heterogeneous carbonate reservoir), namely the permeability-porosity correlation, the hydraulic units (HU’s) and global hydraulic elements (GHE

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

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t