The aim of this study is to investigate the antibacterial capabilities of different coating durations of three nanoparticle (NP) coatings: molybdenum (Mo), tantalum (Ta), and zinc oxide (ZnO), and their effects on the surface characteristics of 316L stainless steel (SS). The coated substrates underwent characterization utilizing field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectrometry (EDX), and X-ray diffractometer (XRD) techniques. The antibacterial efficacy of NPs was evaluated using the agar diffusion method. The FE-SEM and EDX images confirmed the presence of nano-sized particles of Mo, Ta, and ZnO on the surface of the substrates with perfectly symmetrical spheres and a uniform distribution of

The aim of this paper is to present method for solving ordinary differential equations of eighth order with two point boundary conditions. We propose two-point osculatory interpolation to construct polynomial solution.

The eggshell cuticle is the proteinaceous outermost layer of the eggshell which regulates water exchange and protects against entry of micro-organisms. Outer eggshell and cuticle protein was extracted from domestic chicken. The aim of the research is to find out the effect of the treated and untreated nano particles of egg shells with micro wave cold plasma on the effectiveness of E. coli (negative bacteria) that infect the skin and measure the diameter of bacterial inhibition zone, the eggshell has been prepared by a chemical method (sol gel) and measure the level of acidity and the PH is neutral. The result of Atomic Force Microscope (AFM) shows that the particles diameters become smaller with nano-particles solution than for egg

The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima

Fractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.

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