In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

                The research aims to highlight the role played by the target costing technique as an administrative technique that is compatible with the rapid developments and changes in the external environment, with the information and scientific foundations it provides in the allocation of indirect costs and the accuracy in measuring the cost from the start of the project planning process up to the production process and indicating the extent of its impact on decisions Pricing in a way that contributes to the rationalization of pricing decisions in economic units in the light of intense competition and the multiplicity of alternatives.

Hydrophobic silica aerogels were successfully preparation by an ambient pressure drying method from sodium silicate (Na2SiO3) with different pH values (5, 6, 7, 8, 9 and 10). In this study, acidic HCl (1M), a basic NH4OH (1M) were selected as a catalyst to perform the surface modification in a TMCS (trimethylchlorosilane) solution. The surface chemical modification of the aerogels was assured by the Fourier transform infrared (FTIR) spectroscopic studies. Other physical properties, such as pore volume and pore size and specific surface area were determined by Brunauer-Emmett- Teller (BET) method. The effect of pH values on the bulk density of aerogel. The sol–gel parameter pH value in the sol, have marked effects on the physical proper

Cr2O3 thin films have been prepared by spray pyrolysis on a glass substrate. Absorbance and transmittance spectra were recorded in the wavelength range (300-900) nm before and after annealing. The effects of annealing temperature on absorption coefficient, refractive index, extinction coefficient, real and imaginary parts of dielectric constant and optical conductivity were expected. It was found that all these parameters increase as the annealing temperature increased to 550°C.

Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse

In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.