Photometric techniques are one of the fundamentals and of great importance in the study of astronomical phenomena, including galaxies, and has witnessed a wide development during the last 100 years in equipment, sensitivity and accuracy in data analysis, especially after the direction toward space telescopes and the widespread use of a CCD camera. Therefore, in this research, an analytical study will be made to compare two types of galaxies, which are spiral and lenticular galaxies, using photometric techniques and compare the photometric parameters of each type with tables and illustrations. An analysis of the morphological of the two galaxies was done by using the Least Square Fitting Method, and it was fully explained in

Since the beginning of mankind, the view of the sky was present through observations with the naked eye, then it developed with time, and the sciences and tools of astronomical observations developed, including photometric measurements, which reached a high degree of accuracy in describing various cosmic phenomena, including the study of galaxies, their composition, and the differences between them, and from here the importance of this study emerged, to determine the differences between two distinct types of classification of galaxies, which are normal and barred spiral galaxies, where two galaxies NGC 4662 and NGC 2649 were chosen that represented certain types of galaxies to study the morphological structure of the two galaxies, a

The aim of this research is to recognize the tasks undertaken by   the   headmasters   of   intermediate   schools   concerning   time- administration,   in   accordance   to   the   viewpoints   of   the headmasters   of   intermediate   schools   in   the   Administration   of Education   of   Al-Karkh   the   Third.   The   sample   of   this   research consists   of   (60)   headmasters   and &n

The integer simulation and development finite impulse response (FIR) filters taking into account the possibilities of their realization on digital integer platforms are considered. The problem statement and solution of multifunctional synthesis of digital FIR filters such a problem on the basis of the numerical methods of integer nonlinear mathematical programming are given. As an several examples, the problem solution of synthesis FIR-filters with short coefficient word length  has been given. The analysis of their characteristics is resulted. The paper discusses issues of modeling and synthesis of digital FIR filters with provision for the possibilities of their implementation on digital platforms with integer computation arithme

     Machine learning-based techniques are used widely for the classification of images into various categories. The advancement of Convolutional Neural Network (CNN) affects the field of computer vision on a large scale. It has been applied to classify and localize objects in images. Among the fields of applications of CNN, it has been applied to understand huge unstructured astronomical data being collected every second. Galaxies have diverse and complex shapes and their morphology carries fundamental information about the whole universe. Studying these galaxies has been a tremendous task for the researchers around the world. Researchers have already applied some basic CNN models to predict the morphological classes

In this study, two active galaxies (NGC4725, NGC4639) have been chosen to study their morphological and photometric properties, by using the IRAF ISOPHOTE ELLIPS task with griz-filters. Observations are obtained from the Sloan Digital Sky Survey (SDSS) which reaches now to the DATA Release (DR14). The data reduction of all images (bias and flat field) has been done by SDSS Pipeline. The surface photometric investigation was performed like the magnitude. Together with isophotal contour maps, surface brightness profiles and a bulge/disk decomposition of the images of the galaxies, although the disk position angle, ellipticity, and inclination of the galaxies have been done. Also, the color of galaxies was studied, where chromatic distribution

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

Ninety eight mobile samples, (54) galaxy phone and (44) I phone, were swabbed for bacterial culture determination by culturing on MacConky agar , Blood agar , Mannitol salt agar , Muller Hinton agar .Staphylococcuswas the highest frequent isolated bacteria from Galaxy phone (33%) and I phone (37%). This study revealed that galaxy phone appears less contaminated with bacteria, the ratio of non-contaminated devices is (44%) when compared with I phone (9%). Sensitivity test showed that Ogmintin have the lowest effect on Staphylococcusisolated from both type of devices while cefitriaxone have the highest effect. DNA of isolate from galaxy 31 that exhibit highest resistance against antibiotics was extracted and 16S rRNA gene was polymerized by P

<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt&amp; pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by usi