The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussia

Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

The research aims to monitor and analyze the visual and symbolic features, derived from the Omani heritage, and inspired by the concept of local identity, for a selection of contemporary Omani graphic art works, which represent a mixed, multi-category of research sample, comprising three levels: the works of professional Omani artists, and the works of young artists and specialized students, as well as the work of a number of active academics in the field of graphic theorizing and teaching. The sample is also divided - in terms of technical classification - into a category of works executed using traditional engraving and printing media, and a category of works executed using modern and digital graphic printing media.
Through the da

Heritage reflects peoples' memory and essence of nations. Thus, this divan was really the material and tool for writers in general and poets in specific both in their artificial innovations . Accordingly, modern writers have endeavored to bring heritage back in all its details and occurrences. Abdullwahab Al-Bayati's experience had reflected his innovative and strong link with the humanitarian heritage, in that heritage in view of Al-Bayati means both the humanitarian expertise and gains that are able to extend from past to future passing through the present.From this, the poet had not disconnected his strong link with the Arab poetic heritage .Thus, the poet had utilized the Arab poetic heritage in expressing on the Arab contrary realit

The main goal of this in vivo study was to evaluate the effect of 532nm Q-switched Nd: YAG Laser in combination with Human Serum Albumin 20% concentration (as a welding aid) on the liver tissue repair clinically, and histologically. The animals used in this study were 21 male rabbits divided into three main groups: control group (3 rabbits), conventionally treated group (9 rabbits) and Laser treated group (9 rabbits). Each two main groups (conventional and laser treated) consist of three sub-groups depending on the response evaluation at three different periods. The Laser group was treated using 532nm Q-switched Nd: YAG laser after adding human serum albumin immediately on the incised liver’s tissue. The energy of was 460mJ, and 4Hz fr

This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

Two oil wells were tested to find the abnormal pressure zones using sonic log technique. We found that well Abu-Jir-3 and Abu-Jir-5 had an abnormal pressure zones from depth 4340 to 4520 feet and 4200 to 4600 feet, respectively. The maximum difference between obtained results and the field measured results did not exceed 2.4%.
In this paper, the formation pressures were expressed in terms of pressure gradient which sometimes reached up to twice the normal pressure gradient.
Drilling and developing such formations were dangerous and expensive.
The plotted figures showed a clear derivation from the normal trend which confirmed the existence of abnormal pressure zones.