Soil stabilization with stone powder is a good solution for the construction of subgrade for road way and railway lines, especially under the platforms and mostly in transition zones between embankments and rigid structures, where the mechanical properties of supporting soils are very influential. Stone powder often has a unique composition which justifies the need for research to study the feasibility of using this stone powder type for ground improvement applications. This paper presents results from a comprehensive laboratory study carried out to investigate the feasibility of using stone powder for improvement of engineering properties of clays.

The stone powder contains bassanite (CaSO₄. ½ H

Recently, the development and application of the hydrological models based on Geographical Information System (GIS) has increased around the world. One of the most important applications of GIS is mapping the Curve Number (CN) of a catchment. In this research, three softwares, such as an ArcView GIS 9.3 with ArcInfo, Arc Hydro Tool and Geospatial Hydrologic Modeling Extension (Hec-GeoHMS) model for ArcView GIS 9.3, were used to calculate CN of (19210 ha) Salt Creek watershed (SC) which is located in Osage County, Oklahoma, USA. Multi layers were combined and examined using the Environmental Systems Research Institute (ESRI) ArcMap 2009. These layers are soil layer (Soil Survey Geographic SSURGO), 30 m x 30 m resolution of Digital Elevati

The development of analytical techniques is required for the accurate and comprehensive detection and measurement of antibiotic contamination in the environment. Metronidazole is a common antibacterial, antiprotozoal, and antibiotic drug. Thiamine is a vital biological and medicinal ingredient that is involved in the metabolism of proteins, fats, and carbohydrates that produce energy. The study aims to identify the drugs in a mixture without separation to provide more information to confirm if a drug is present in a combination. Metronidazole and thiamine are two examples of pharmaceutical and environmental samples that can be identified using spectrophotometric techniques because of their low cost and simplicity of use. The operati

Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essentia

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

Background: In dentistry, dentist takes the advantages of soft lining materials due to the viscoelastic properties. The major problem is the adhesion of the soft liner with the denture base material. Materials and Methods: Heat cured of high impact acrylic resin specimens prepared with dimensions 75x13x13mm for shear bond strength test, soft lining material (Refit and Mollosil) with a 3-mm thickness and used to join each two acrylic blocks. Also four specimens with the same previous dimensions utilized for chemical and physical surface analysis. The specimens grouped as control (without plasma) and experiment (with oxygen plasma) treated high impact acrylic specimens. Results: Plasma treatment increased the shear bond strength for both Refi

This researchpaper includes the incorporation of Alliin at various energy levels and angles 

With Metformin using Gaussian 09 and Gaussian view 06. Two computers were used in this work. Samples were generated to draw, integrate, simulate and measure the value of the potential energy surface by means of which the lowest energy value was (-1227.408au). The best correlation compound was achieved between Alliin and Metformin through the low energy values where the best place for metformin to b