Shallow foundations are usually used for structures with light to moderate loads where the soil underneath can carry them. In some cases, soil strength and/or other properties are not adequate and require improvement using one of the ground improvement techniques. Stone column is one of the common improvement techniques in which a column of stone is installed vertically in clayey soils. Stone columns are usually used to increase soil strength and to accelerate soil consolidation by acting as vertical drains. Many researches have been done to estimate the behavior of the improved soil. However, none of them considered the effect of stone column geometry on the behavior of the circular footing. In this research, finite ele

The semiconductor ZnO is one of II – VI compound group, it is prepare as thin films by using chemical spray pyrolysis technique; the films are deposited onto glass substrate at 450 °C by using aqueous zinc chloride as a spray solution of molar concentration 0.1 M/L. Sample of the prepared film is irradiating by Gamma ray using CS 137, other sample is annealed at 550°C. The structure of the irradiated and annealed films are analyzed with X-ray diffraction, the results show that the films are polycrystalline in nature with preferred (002) orientation. The general morphology of ZnO films are imaged by using the Atomic Force Microscope (AFM), it constructed from nanostructure with dimensions in order of 77 nm.
The optical properties o

Cadmium oxide (CdO) thin films were deposited using the sequencing ion layer adsorption and reaction (SILAR) method. In this study, the effect of the pH value of an aqueous solution of cadmium acetate at a concentration of 0.2 mol of the cadmium oxide film was determined. The solution source for the cadmium oxide film was cadmium ions and an aqueous ammonia solution. The CdO films were deposited on glass substrates at a temperature of 90 ℃. The cadmium oxide film thickness was determined by the weight difference method at pH values ​​(7.2, 8.2). X-ray diffraction (XRD) and scanning electron microscopy (SEM) showed that the size of the crystals increased with the increase in the solution (pH). While the UV-visible spectra of the fil

Pore volume, pore diameter, and pore volume distribution of three of Iraqi natural clay deposites were measured using mercury intrusion porosimetry .The clays are white kaolin, colored kaolin, and bentonite .The results showed that the variation of the pore area of the clay deposites followed the following order :- Coloured Kaolin > White Kaolin > Bentonite While the pore volume may be arranged as in the following sequence:- White Kaolin > Coloured Kaolin >Bentonite Also , Bentonite exhibits the narrow range pore size distribution than the white and coloured kaolin.

Volleyball is one of the sports that require physical and skill abilities thus many teaching models appeared to teach these abilities like group investigation model. The research aimed at identifying the effect of group investigation model on learning underarm and overhead passing in volleyball. The researchers hypothesized statistical differences between pre and posttests in learning underarm and overhead passing in volleyball as well as differences in posttests of controlling and experimental groups in learning underarm and overhead passing in volleyball. The researcher used the experimental method on (30) second year female students of physical education and sport sciences college/ university of Baghdad. Group investigation model was app

optical properties of pure poly(vinyl Alcohol) films and poly(vinyl Alcohol) doped with methyl red were study, different percentage prepared with constant thickness using casting technique. Absorption, Transmission spectra have been recorded in order to study the optical parameters such as absorption coefficient, energy gap, refractive index, Extinction coefficient and dispersion parameters were measured in the wavelength range (200-800)nm. This study reveals that the optical properties of PVA affect by increasing the impurity concentration.

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow