In this research we prepared PbS thin films with vacuum thermo evaporation process and  chemical spray pyrolysis.         Structure properties were studied for PbS thin films through (XRD) measurement. PbS thin films growth appear as Polycrystalline cubic and sharp peak with directional (200) then  calculated   Lattice constant (a) and the values are (5.9358)Ã… for (PbS) films prepared by thermo evaporation , (2.978-5.969 Ã…) for films prepared by chemical spray pyrolysis at temperature degree   (553K , 573K)  sequence .Then it was found that the grain size for (PbS) thin films prepared by thermo evaporation is (335.81)Ã… while the grai

The splicing design of the existing road and the new road in the expansion project is an important part of the design work. Based on the analysis of the characteristics and the load effect of pavement structure on splicing, this paper points out that tensile crack or shear failure may occur at the splicing under the repeated action of the traffic load on the new/old pavement. According to the current structure design code of asphalt pavement in China, it is proposed that the horizontal tensile stress at the bottom of the splicing layer and the vertical shear stress at other layers of the splicing line should be controlled by adjusting the position and size of the excavated steps in addition to the conventional design ind

The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional

According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

     The current study examined the use of Sansevieria plant leaves extract as an environmentally acceptable, inexpensive, and safe green approach for creating titanium dioxide nanoparticles (NPs). Batch studies have been used to test the particles' capacity to bind to the azo dye congo red (CR), which has been adsorbed from its aqueous solution. The effects of many factors, including the weight of TiO2 NPs, the contact duration to reach equilibrium, the concentration of CR, temperature, and pH, have been investigated. Both the Freundlich and Langmuir models were used to analyze experimental results. According to the high values of the Freundlich model's correlation coefficient R², it is discovered that th

Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each paramet